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Each system has its own names for channels, regions, and audiences, its own date format, and its own copy of the biggest campaigns. So nobody has a single, trustworthy view of what's launching, and teams end up hitting the same audience with competing offers in the same week.\u003C/p\u003E\n","\u003Cp\u003EIn this hands-on lab you'll fix that for \u003Cstrong\u003EMeridian Stay\u003C/strong\u003E, a fictional global hotel brand, just as its holiday season plan is going live. You'll land the raw campaign exports in open \u003Cstrong\u003EApache Iceberg\u003C/strong\u003E tables, use \u003Cstrong\u003ESnowflake CoCo\u003C/strong\u003E to clean and standardize them, and surface every audience collision on a live collision heatmap. Then you'll hand the result to the whole team through \u003Cstrong\u003ESnowflake CoWork\u003C/strong\u003E, so anyone can ask \u003Cem\u003E"What's launching in APAC next month?"\u003C/em\u003E and get an answer in seconds.\u003C/p\u003E\n","\u003Ch3\u003EPrerequisites\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ENo coding experience required. CoCo writes the SQL; you describe what you want and review the result.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to clone a public GitHub repo as a Git-backed Snowflake Workspace and run a notebook inside it\u003C/li\u003E\u003Cli\u003EHow to land raw data in \u003Cstrong\u003ESnowflake-managed Apache Iceberg tables\u003C/strong\u003E, an open format that other engines can read\u003C/li\u003E\u003Cli\u003EHow to use \u003Cstrong\u003ECoCo\u003C/strong\u003E to standardize labels, parse dates and budgets, remove duplicates, and filter out cancelled campaigns\u003C/li\u003E\u003Cli\u003EHow to find audience collisions across teams and channels\u003C/li\u003E\u003Cli\u003EHow to run and customize a \u003Cstrong\u003EStreamlit\u003C/strong\u003E collision heatmap with CoCo\u003C/li\u003E\u003Cli\u003EHow to create a \u003Cstrong\u003ESemantic View\u003C/strong\u003E with CoCo and a \u003Cstrong\u003ECortex Agent\u003C/strong\u003E backed by it\u003C/li\u003E\u003Cli\u003EHow to investigate business questions in plain language in \u003Cstrong\u003ESnowflake CoWork\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Need\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA free Snowflake trial account: \u003Ca href=\"https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&trial=student&cloud=aws&region=us-east-2&utm_campaign=introtosnowflake&utm_cta=developer-guides\"\u003Ehttps://signup.snowflake.com/\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EThe companion GitHub repo: \u003Ca href=\"https://github.com/Snowflake-Labs/expedition-2026-day-2-hol\"\u003Ehttps://github.com/Snowflake-Labs/expedition-2026-day-2-hol\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Build\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA governed, deduplicated campaign list built from three messy exports, stored as Iceberg\u003C/li\u003E\u003Cli\u003EA table of every audience collision in Meridian Stay's November 2026 – January 2027 plan\u003C/li\u003E\u003Cli\u003EA live collision heatmap app\u003C/li\u003E\u003Cli\u003EA Cortex Agent that answers campaign-planning questions in Snowflake CoWork\u003C/li\u003E\u003C/ul\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EOpen a Snowflake Trial Account\u003C/h2\u003E\n","\u003Cp\u003EDuration: 3\u003C/p\u003E\n","\u003Cp\u003ETo complete this lab, you'll need a Snowflake account. A free Snowflake trial account works well. To open one:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ENavigate to \u003Ca href=\"https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&trial=student&cloud=aws&region=us-east-2&utm_campaign=introtosnowflake&utm_cta=developer-guides\"\u003Ehttps://signup.snowflake.com/\u003C/a\u003E. This link pre-selects \u003Cstrong\u003EAWS\u003C/strong\u003E and the \u003Cstrong\u003EUS East (Ohio)\u003C/strong\u003E region for you.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EComplete the first page of the form.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EOn the next section, set the Snowflake edition to \u003Cstrong\u003EEnterprise (Most popular)\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EConfirm \u003Cstrong\u003EAWS – Amazon Web Services\u003C/strong\u003E is selected as the cloud provider (pre-filled by the link).\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EConfirm \u003Cstrong\u003EUS East (Ohio)\u003C/strong\u003E is selected as the region (pre-filled by the link).\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EComplete the rest of the form and click \u003Cstrong\u003EGet started\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EUnderstand the Scenario\u003C/h2\u003E\n","\u003Cp\u003EDuration: 2\u003C/p\u003E\n","\u003Cp\u003EYou're on the marketing operations team at Meridian Stay, and it's November 2026. Last year, the Loyalty team and Brand Marketing both targeted rewards members with competing Black Friday offers, and nobody noticed until the emails went out. Leadership wants to know: is it about to happen again?\u003C/p\u003E\n","\u003Cp\u003EThe root cause is simple: campaign plans live in three systems that don't agree with each other.\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ESource system\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EExport\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EHow it's messy\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAd platforms\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ccode\u003Epaid_media_export.csv\u003C/code\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EChannel codes like \u003Ccode\u003Efb_ads\u003C/code\u003E and \u003Ccode\u003Egoogle_ads\u003C/code\u003E, region \u003Ccode\u003ENA\u003C/code\u003E, budgets stored as text (\u003Ccode\u003E"$65,000"\u003C/code\u003E), and two rows exported twice\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EEmail & SMS platform (e.g., Marketo, HubSpot, Braze)\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ccode\u003Eemail_sms_export.csv\u003C/code\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ccode\u003EMM/DD/YYYY\u003C/code\u003E dates, regions like \u003Ccode\u003EUS & Canada\u003C/code\u003E, segments like \u003Ccode\u003ECorporate Segment\u003C/code\u003E\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ECRM\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ccode\u003Ecrm_campaigns_export.csv\u003C/code\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ccode\u003ENov 02, 2026\u003C/code\u003E dates, copies of the biggest paid campaigns (one with a trailing space, one in ALL CAPS), and a \u003Cstrong\u003Ecancelled\u003C/strong\u003E campaign, \u003Cem\u003EVeterans Day Weekend Blitz\u003C/em\u003E, that was never removed\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Ch3\u003EHere's the plan\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\u003Cstrong\u003ELand\u003C/strong\u003E the three exports, exactly as they arrived, in \u003Cstrong\u003EApache Iceberg\u003C/strong\u003E tables.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EClean\u003C/strong\u003E them with CoCo into one governed campaign list, also stored as Iceberg.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EFind\u003C/strong\u003E every audience collision: two campaigns aimed at the same audience in the same region on overlapping dates.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ESee\u003C/strong\u003E where collisions cluster on a live heatmap and put a dollar value on them.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAsk\u003C/strong\u003E planning questions in plain language through a Cortex Agent in \u003Cstrong\u003ESnowflake CoWork\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EEverything through step 4 runs from a \u003Cstrong\u003Esingle notebook\u003C/strong\u003E (\u003Ccode\u003Elab.ipynb\u003C/code\u003E) and a pre-built app in the companion repo. Step 5 is done in the Snowsight UI. Let's get started!\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESet Up Your Workspace\u003C/h2\u003E\n","\u003Cp\u003EDuration: 5\u003C/p\u003E\n","\u003Cp\u003EThere are no setup scripts to run and no SQL worksheets to open first. Your first action is to create a \u003Cstrong\u003EGit-backed Workspace\u003C/strong\u003E that clones the companion repo. The repo contains the notebook you'll run (\u003Ccode\u003Elab.ipynb\u003C/code\u003E), the three campaign exports (\u003Ccode\u003Edata/\u003C/code\u003E), and the collision heatmap app (\u003Ccode\u003Ecampaign_timeline/\u003C/code\u003E).\u003C/p\u003E\n","\u003Ch3\u003ESign in as ACCOUNTADMIN\u003C/h3\u003E\n","\u003Cp\u003EMake sure you are signed into your trial account. Confirm your active role is \u003Cstrong\u003EACCOUNTADMIN\u003C/strong\u003E: click your name in the bottom-left corner of Snowsight to see the active role. If it shows a different role, choose \u003Cstrong\u003ESwitch role\u003C/strong\u003E → \u003Cstrong\u003EACCOUNTADMIN\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/role.png?v=ce00a69e\" alt=\"role\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ECreate a Git-backed Workspace\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn Snowsight, navigate to \u003Cstrong\u003EProjects » Workspaces\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick the \u003Cstrong\u003E+\u003C/strong\u003E icon next to \u003Cstrong\u003EWorkspaces/Databases\u003C/strong\u003E → \u003Cstrong\u003ECreate new Git workspace\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/gitworkspace.png?v=ce00a69e\" alt=\"gitworkspace\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EFill out the modal:\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003ERepository URL:\u003C/strong\u003E \u003Ccode\u003Ehttps://github.com/Snowflake-Labs/expedition-2026-day-2-hol\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EWorkspace name:\u003C/strong\u003E anything you like (e.g., \u003Ccode\u003Ecampaign-planning\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAPI integration:\u003C/strong\u003E click \u003Cstrong\u003E+ / Create new\u003C/strong\u003E and provide:\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EName:\u003C/strong\u003E \u003Ccode\u003EGITHUB_MERIDIAN_LAB\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAllowed prefixes:\u003C/strong\u003E \u003Ccode\u003Ehttps://github.com/Snowflake-Labs\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003ECheck \u003Cstrong\u003EPublic repository\u003C/strong\u003E.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/gitrepository.png?v=ce00a69e\" alt=\"gitrepository\"\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/apiintegration.png?v=ce00a69e\" alt=\"apiintegration\"\u003E\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EWhat just happened?\u003C/strong\u003E The Workspace modal created a Git API integration for you, a one-time step that tells Snowflake which GitHub organization is an allowed source for Git-backed Workspaces.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EThe Workspace opens with the repo's files visible in the file explorer on the left.\u003C/p\u003E\n","\u003Ch3\u003EOpen the notebook and set its compute\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the Workspace file explorer, open \u003Cstrong\u003E\u003Ccode\u003Elab.ipynb\u003C/code\u003E\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003EConnect\u003C/strong\u003E next to the Run button and select \u003Cstrong\u003ECreate and connect\u003C/strong\u003E. Wait for the status bar at the bottom of the notebook to show \u003Cstrong\u003EConnected\u003C/strong\u003E before proceeding.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/connected.png?v=ce00a69e\" alt=\"connected\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003E\n","\u003Cp\u003ESet the notebook's active \u003Cstrong\u003Erole\u003C/strong\u003E and \u003Cstrong\u003Ewarehouse\u003C/strong\u003E using the \u003Cstrong\u003Erole & warehouse picker\u003C/strong\u003E at the top of the Notebooks editor:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003ERole:\u003C/strong\u003E \u003Cstrong\u003EACCOUNTADMIN\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EWarehouse:\u003C/strong\u003E \u003Cstrong\u003ECOMPUTE_WH\u003C/strong\u003E (the default warehouse in every trial account)\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EWork top-to-bottom through the notebook. Markdown cells explain each step; code cells contain the SQL, some of which you'll generate yourself with CoCo. Run a cell with \u003Cstrong\u003E▶\u003C/strong\u003E (or \u003Cstrong\u003EShift+Enter\u003C/strong\u003E).\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EThroughout the lab, the notebook shows a \u003Cstrong\u003ECoCo prompt\u003C/strong\u003E in the markdown cell directly above each empty SQL cell. You can use the prompts from there or copy them from this guide. They should be identical or similar.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EOpen the CoCo panel\u003C/h3\u003E\n","\u003Cp\u003EOpen the \u003Cstrong\u003ECoCo\u003C/strong\u003E chat panel from the Workspace toolbar. You'll send it prompts throughout the lab.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/coco.png?v=ce00a69e\" alt=\"coco\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EKey principle:\u003C/strong\u003E Use CoCo to generate the hard parts and understand why. The workflow is: describe → generate → compare → run. After CoCo generates SQL, compare it against the \u003Cstrong\u003EExpected output\u003C/strong\u003E shown in the notebook. If they match, click \u003Cstrong\u003EAllow\u003C/strong\u003E to run it. Optionally, copy the SQL into the notebook cell for future reference.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ERun the setup cell\u003C/h3\u003E\n","\u003Cp\u003EThe first SQL cell in the notebook (\u003Cstrong\u003E\u003Ccode\u003Esetup\u003C/code\u003E\u003C/strong\u003E) creates the \u003Ccode\u003EMERIDIAN_STAY\u003C/code\u003E database with three schemas:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ccode\u003ERAW\u003C/code\u003E: the exports, exactly as they arrived\u003C/li\u003E\u003Cli\u003E\u003Ccode\u003ECURATED\u003C/code\u003E: clean, governed tables\u003C/li\u003E\u003Cli\u003E\u003Ccode\u003EANALYTICS\u003C/code\u003E: the semantic view and agent\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EIt also grants the Cortex Agent privileges your role needs later. Run the \u003Cstrong\u003E\u003Ccode\u003Esetup\u003C/code\u003E\u003C/strong\u003E cell before continuing. You should see \u003Cem\u003E"Statement executed successfully."\u003C/em\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/setupcell.png?v=ce00a69e\" alt=\"setupcell\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ELand Raw Exports\u003C/h2\u003E\n","\u003Cp\u003EDuration: 7\u003C/p\u003E\n","\u003Cp\u003EThe first step is to get the raw exports into Snowflake \u003Cstrong\u003Ewithout changing them\u003C/strong\u003E, so you always have the original to compare against.\u003C/p\u003E\n","\u003Ch3\u003EWhy Apache Iceberg?\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EApache Iceberg\u003C/strong\u003E is an open table format. An Iceberg table's data is stored as Parquet files plus open metadata, so other engines (Spark, Trino, DuckDB, and more) can read the same tables through Snowflake Horizon Catalog. Your campaign data stays open instead of being locked into one tool, which matters when the data science team, an agency, or a partner platform needs it too.\u003C/p\u003E\n","\u003Cp\u003EIn this lab you'll use \u003Cstrong\u003ESnowflake-managed Iceberg tables\u003C/strong\u003E (\u003Ccode\u003ECATALOG = 'SNOWFLAKE'\u003C/code\u003E and \u003Ccode\u003EEXTERNAL_VOLUME = 'SNOWFLAKE_MANAGED'\u003C/code\u003E). Snowflake manages the storage for you, so there's no cloud bucket or IAM setup.\u003C/p\u003E\n","\u003Ch3\u003ECreate the raw tables\u003C/h3\u003E\n","\u003Cp\u003ERun the \u003Cstrong\u003E\u003Ccode\u003Eraw_tables\u003C/code\u003E\u003C/strong\u003E cell. It creates:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EThree raw Iceberg tables, one per export, with every column as \u003Ccode\u003ESTRING\u003C/code\u003E (exactly as exported)\u003C/li\u003E\u003Cli\u003EA CSV file format, \u003Ccode\u003ERAW.CSV_FF\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EAn internal stage, \u003Ccode\u003ERAW.CAMPAIGN_EXPORTS\u003C/code\u003E, to hold the files\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EUpload the export files\u003C/h3\u003E\n","\u003Cp\u003ERun the \u003Cstrong\u003E\u003Ccode\u003Eupload_files\u003C/code\u003E\u003C/strong\u003E Python cell. It copies the three CSVs from the repo's \u003Ccode\u003Edata/\u003C/code\u003E folder into the stage. You should see three files with status \u003Ccode\u003EUPLOADED\u003C/code\u003E.\u003C/p\u003E\n","\u003Ch3\u003ESTEP 1 — Load the exports\u003C/h3\u003E\n","\u003Cp\u003E\u003Ccode\u003ECOPY INTO\u003C/code\u003E is Snowflake's bulk-loading command. It reads files from a stage and inserts them into a table, and it works the same way whether the target is a standard table or an Iceberg table.\u003C/p\u003E\n","\u003Cp\u003ESend this prompt to CoCo. Compare the output against the expected output in the notebook. If they match, click \u003Cstrong\u003EAllow\u003C/strong\u003E to run it.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Load the three CSV files in the stage @MERIDIAN_STAY.RAW.CAMPAIGN_EXPORTS into their matching Iceberg tables in MERIDIAN_STAY.RAW: paid_media_export.csv into PAID_MEDIA_EXPORT, email_sms_export.csv into EMAIL_SMS_EXPORT, and crm_campaigns_export.csv into CRM_CAMPAIGNS_EXPORT. Use the file format MERIDIAN_STAY.RAW.CSV_FF and load the columns in file order."\u003C/em\u003E\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/firstprompt.png?v=ce00a69e\" alt=\"firstprompt\"\u003E\u003C/p\u003E\n","\u003Cp\u003EYou should see \u003Cstrong\u003E16\u003C/strong\u003E, \u003Cstrong\u003E10\u003C/strong\u003E, and \u003Cstrong\u003E7\u003C/strong\u003E rows loaded. If CoCo's first attempt fails and it retries with a corrected statement, that's normal: it reads the error and fixes its own SQL.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESeeing \u003Ccode\u003EMATCH_BY_COLUMN_NAME = NONE\u003C/code\u003E at the end of each statement?\u003C/strong\u003E That's fine. It tells Snowflake to load columns by position, which is the default and exactly what \u003Cem\u003E"in file order"\u003C/em\u003E asks for.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ESee the mess\u003C/h3\u003E\n","\u003Cp\u003ERun the \u003Cstrong\u003E\u003Ccode\u003Epeek_raw\u003C/code\u003E\u003C/strong\u003E cell. It lines up all 33 raw rows from the three exports in one grid, sorted by campaign name so copies of the same campaign sit next to each other. Scroll through and notice:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cem\u003EThanksgiving Getaway Sale\u003C/em\u003E appears \u003Cstrong\u003Ethree times\u003C/strong\u003E: twice in the ad platform export (a re-export duplicate) and once in the CRM, with a trailing space.\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EBlack Friday Mega Sale\u003C/em\u003E appears twice, once in ALL CAPS.\u003C/li\u003E\u003Cli\u003EThe same channel is \u003Ccode\u003Efb_ads\u003C/code\u003E in one system and \u003Ccode\u003ESocial Media\u003C/code\u003E in another; the same region is \u003Ccode\u003ENA\u003C/code\u003E, \u003Ccode\u003EUS & Canada\u003C/code\u003E, or \u003Ccode\u003EN. America\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EThree date formats: \u003Ccode\u003E2026-11-02\u003C/code\u003E, \u003Ccode\u003E11/09/2026\u003C/code\u003E, and \u003Ccode\u003ENov 02, 2026\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EBudgets like \u003Ccode\u003E"$65,000"\u003C/code\u003E are text, not numbers.\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EVeterans Day Weekend Blitz\u003C/em\u003E has a status of \u003Cstrong\u003ECancelled\u003C/strong\u003E, but it's still in the list.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EYou can't find collisions until all three systems speak the same language, and that's next.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EClean and Standardize With CoCo\u003C/h2\u003E\n","\u003Cp\u003EDuration: 12\u003C/p\u003E\n","\u003Cp\u003ENow you'll turn three messy exports into one governed campaign list. This usually takes a marketing ops analyst a day of spreadsheet work. With CoCo, you describe the rules in plain language and review the SQL it writes.\u003C/p\u003E\n","\u003Ch3\u003EThe rules\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EOne vocabulary.\u003C/strong\u003E Every channel, region, and audience maps to a single standard label.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EReal dates and numbers.\u003C/strong\u003E Three date formats become real \u003Ccode\u003EDATE\u003C/code\u003E values, and \u003Ccode\u003E"$65,000"\u003C/code\u003E becomes \u003Ccode\u003E65000.00\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ENo duplicates.\u003C/strong\u003E A campaign that appears in more than one system, or twice in the same export, is kept once. The system of record (ad platforms or the email & SMS platform) wins over the CRM copy.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ENo cancelled campaigns.\u003C/strong\u003E A cancelled CRM campaign shouldn't show up on anyone's plan.\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ESTEP 2 — Let CoCo find the mess\u003C/h3\u003E\n","\u003Cp\u003EBefore building anything, ask CoCo to compare the three sources. It queries the raw tables itself and shows you how differently each system describes the \u003Cem\u003Esame\u003C/em\u003E things.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Compare how the three tables in MERIDIAN_STAY.RAW label channel, region, and audience. Map every label to one of these standard values:\u003C/em\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cem\u003EChannel: Paid Social, Paid Search, Display, Email, SMS\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003ERegion: North America, EMEA, APAC, LATAM, Global\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EAudience: Leisure Travelers, Business Travelers, Families, Loyalty Members, Meeting Planners, Wellness Seekers, All Guests\u003C/em\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cem\u003EAlso point out how dates and budgets are formatted differently, and any campaigns whose status means they shouldn't be on the plan."\u003C/em\u003E\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/secondprompt.png?v=ce00a69e\" alt=\"secondprompt\"\u003E\u003C/p\u003E\n","\u003Cp\u003ECoCo should map, for example, \u003Ccode\u003Efb_ads\u003C/code\u003E, \u003Ccode\u003Epaid_social\u003C/code\u003E, and \u003Ccode\u003ESocial Media\u003C/code\u003E to \u003Cstrong\u003EPaid Social\u003C/strong\u003E, and \u003Ccode\u003ENA\u003C/code\u003E, \u003Ccode\u003EUS & Canada\u003C/code\u003E, and \u003Ccode\u003EN. America\u003C/code\u003E to \u003Cstrong\u003ENorth America\u003C/strong\u003E. It should also call out the three date formats, the text budgets, and the cancelled \u003Cem\u003EVeterans Day Weekend Blitz\u003C/em\u003E. It may mention the \u003Cstrong\u003EDraft\u003C/strong\u003E \u003Cem\u003ETokyo Business District Launch\u003C/em\u003E too; drafts are still planned, so it stays. The full expected mapping is in the notebook.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EWhy give CoCo the standard values?\u003C/strong\u003E They're business decisions, like "\u003Ccode\u003ECorporate Segment\u003C/code\u003E means Business Travelers." Listing them is how you make sure CoCo applies \u003Cem\u003Eyour\u003C/em\u003E team's vocabulary instead of inventing its own.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ESTEP 3 — Build the unified CAMPAIGNS table\u003C/h3\u003E\n","\u003Cp\u003EIn the \u003Cstrong\u003Esame CoCo conversation\u003C/strong\u003E, send this prompt. CoCo reuses the mapping from STEP 2 and writes the SQL. Your SQL may not match the expected output in the notebook word for word, and that's fine; the check cell is what tells you it's right. Click \u003Cstrong\u003EAllow\u003C/strong\u003E to run it.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Using that mapping, create a Snowflake-managed Iceberg table MERIDIAN_STAY.CURATED.CAMPAIGNS (EXTERNAL_VOLUME = 'SNOWFLAKE_MANAGED') that combines the three raw tables into one campaign list:\u003C/em\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cem\u003EColumns: campaign_id, campaign_name, channel, region, audience, start_date, end_date, budget_usd, owner_team, status, source_system\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EConvert dates and budgets to real dates and numbers\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EDrop cancelled campaigns\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003ERemove duplicates with the same name (ignoring case and extra spaces) and dates, keeping the ad platform or email & SMS copy over the CRM copy"\u003C/em\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ECheck the result\u003C/h3\u003E\n","\u003Cp\u003ERun the \u003Cstrong\u003E\u003Ccode\u003Echeck_campaigns\u003C/code\u003E\u003C/strong\u003E cell. You should see:\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003Ecampaigns\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003Eunmapped_values\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003Echannels\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003Eregions\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003Eaudiences\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E27\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E0\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E5\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E5\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E7\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Cp\u003EThat's 33 raw rows, minus 5 duplicates and 1 cancelled campaign. If your numbers are different, ask CoCo to fix it rather than editing the SQL yourself:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ccode\u003Eunmapped_values\u003C/code\u003E above 0: \u003Cem\u003E"Which rows in MERIDIAN_STAY.CURATED.CAMPAIGNS have a NULL channel, region, audience, date, or budget? Fix the mapping."\u003C/em\u003E\u003C/li\u003E\u003Cli\u003EMore than 27 campaigns: \u003Cem\u003E"Which campaigns appear more than once in MERIDIAN_STAY.CURATED.CAMPAIGNS? Fix the duplicate removal."\u003C/em\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EShort on time? Paste the expected output from the notebook into the empty cell and run it.\u003C/p\u003E\n","\u003Ch3\u003EBefore and after\u003C/h3\u003E\n","\u003Cp\u003ERun the \u003Cstrong\u003E\u003Ccode\u003Ebefore_after\u003C/code\u003E\u003C/strong\u003E cell. It shows the campaigns that needed the most cleaning, as they arrived in \u003Ccode\u003ERAW\u003C/code\u003E and as they are now in \u003Ccode\u003ECURATED\u003C/code\u003E:\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ELayer\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ESource\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ECampaign\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EChannel\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ERegion\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EAudience\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EStart date\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EBudget\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EStatus\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBefore\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ECRM_CAMPAIGNS_EXPORT\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThanksgiving Getaway Sale \u003Cem\u003E(trailing space)\u003C/em\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESocial Media\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EN. America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELeisure\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENov 02, 2026\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E65000\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EActive\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBefore\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EPAID_MEDIA_EXPORT\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThanksgiving Getaway Sale\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Efb_ads\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENA\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Eleisure\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-02\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$65,000\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E \u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBefore\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EPAID_MEDIA_EXPORT\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThanksgiving Getaway Sale\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Efb_ads\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENA\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003Eleisure\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-02\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$65,000\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E \u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Cstrong\u003EAfter\u003C/strong\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EPaid Media\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThanksgiving Getaway Sale\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EPaid Social\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELeisure Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-02\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E65000.00\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EActive\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Cp\u003EThe same happens for \u003Cem\u003EBlack Friday Mega Sale\u003C/em\u003E (two copies become one), and \u003Cem\u003EVeterans Day Weekend Blitz\u003C/em\u003E has no "after" row at all. Six messy rows become two clean ones.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/beforeafter.png?v=ce00a69e\" alt=\"beforeafter\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ESTEP 4 — Find every audience collision\u003C/h3\u003E\n","\u003Cp\u003EA \u003Cstrong\u003Ecollision\u003C/strong\u003E is two different campaigns that target the same audience, in the same region, on overlapping dates. That's exactly what happened with last year's Black Friday offers.\u003C/p\u003E\n","\u003Cp\u003ESend this prompt to CoCo. Compare the output against the expected output in the notebook, then click \u003Cstrong\u003EAllow\u003C/strong\u003E to run it. The prompt names the columns so that everyone's table matches the Semantic View and CoWork questions later.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Create a Snowflake-managed Iceberg table MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS (EXTERNAL_VOLUME = 'SNOWFLAKE_MANAGED') listing every pair of campaigns in CURATED.CAMPAIGNS that target the same region and audience on overlapping dates. List each pair once.\u003C/em\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cem\u003EColumns: campaign_a_id, campaign_a_name, campaign_b_id, campaign_b_name, region, audience, overlap_start, overlap_end, overlap_days, combined_budget_usd"\u003C/em\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ECheck the result\u003C/h3\u003E\n","\u003Cp\u003ERun the \u003Cstrong\u003E\u003Ccode\u003Echeck_collisions\u003C/code\u003E\u003C/strong\u003E cell. You should see \u003Cstrong\u003E9 rows\u003C/strong\u003E, with \u003Ccode\u003Etotal_collisions\u003C/code\u003E = \u003Cstrong\u003E9\u003C/strong\u003E and \u003Ccode\u003Etotal_combined_budget\u003C/code\u003E = \u003Cstrong\u003E$557,500\u003C/strong\u003E. If you see 18 rows, each pair is listed twice; ask CoCo to \u003Cem\u003E"list each pair only once."\u003C/em\u003E The collisions are (A and B may be swapped in your table):\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ECampaign A\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ECampaign B\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ERegion\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EAudience\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EOverlap starts\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ECombined budget\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAmex Travel Partner Promo\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBusiness Travel Year-End Push\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBusiness Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-09\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$80,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAutumn Weekend Escapes\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThanksgiving Getaway Sale\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELeisure Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-09\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$77,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAmex Travel Partner Promo\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ERoad Warrior Rewards\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBusiness Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-16\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$9,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ERoad Warrior Rewards\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBusiness Travel Year-End Push\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBusiness Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-16\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$89,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELoyalty Double Points Month\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EBlack Friday Mega Sale\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELoyalty Members\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-11-20\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$97,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EEMEA Winter Sun\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELondon Festive Stays\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EEMEA\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELeisure Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-12-01\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$63,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EHoliday Gift Card Push\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EHoliday Family Getaways\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ENorth America\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EFamilies\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-12-05\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$47,500\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAPAC Year-End Flash Sale\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESingapore Staycation Deals\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAPAC\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EFamilies\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2026-12-20\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$40,000\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ETokyo Cherry Blossom Preview\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESydney Summer Kickoff\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EAPAC\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ELeisure Travelers\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E2027-01-10\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E$55,000\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Cp\u003EFive of the nine are in \u003Cstrong\u003ENovember\u003C/strong\u003E, including the answer to leadership's question: \u003Cem\u003ELoyalty Double Points Month\u003C/em\u003E and \u003Cem\u003EBlack Friday Mega Sale\u003C/em\u003E are about to hit rewards members at the same time, again.\u003C/p\u003E\n","\u003Cp\u003ENotice what's \u003Cem\u003Enot\u003C/em\u003E on the list: the cancelled \u003Cem\u003EVeterans Day Weekend Blitz\u003C/em\u003E. Without the clean-up step, it would have raised two false alarms against \u003Cem\u003EThanksgiving Getaway Sale\u003C/em\u003E and \u003Cem\u003EAutumn Weekend Escapes\u003C/em\u003E.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESee Where Collisions Cluster\u003C/h2\u003E\n","\u003Cp\u003EDuration: 9\u003C/p\u003E\n","\u003Cp\u003EA table of collisions is useful. A view the whole team can scan in five seconds is better. The companion repo includes a pre-built \u003Cstrong\u003EStreamlit\u003C/strong\u003E app that turns \u003Ccode\u003ECURATED.CAMPAIGNS\u003C/code\u003E into a \u003Cstrong\u003Ecollision heatmap\u003C/strong\u003E for the whole holiday season.\u003C/p\u003E\n","\u003Ch3\u003ERun the heatmap\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EIn the Workspace file explorer, open \u003Cstrong\u003E\u003Ccode\u003Ecampaign_timeline/streamlit_app.py\u003C/code\u003E\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/streamlitapp.png?v=ce00a69e\" alt=\"streamlitapp\"\u003E\u003C/p\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003EIf a banner says \u003Cem\u003E"This file looks like a Streamlit app, but is missing configuration"\u003C/em\u003E, click \u003Cstrong\u003EConvert to streamlit app\u003C/strong\u003E. The Workspace adds the configuration files the app needs.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/convert.png?v=ce00a69e\" alt=\"convert\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ERun\u003C/strong\u003E. The app runs privately for you on a container runtime and reads straight from \u003Ccode\u003EMERIDIAN_STAY.CURATED.CAMPAIGNS\u003C/code\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/heatmap.png?v=ce00a69e\" alt=\"heatmap\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EHow to read it\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EEach \u003Cstrong\u003Erow\u003C/strong\u003E is a region and audience pair, like \u003Cem\u003ENorth America · Business Travelers\u003C/em\u003E. The app opens on only the pairs with competing offers, hottest at the top.\u003C/li\u003E\u003Cli\u003EEach \u003Cstrong\u003Ecolumn\u003C/strong\u003E is a week, from November 2026 through January 2027.\u003C/li\u003E\u003Cli\u003EA \u003Cstrong\u003Egrey\u003C/strong\u003E cell means one campaign is reaching that audience that week, which is fine. An \u003Cstrong\u003Eorange (2)\u003C/strong\u003E or \u003Cstrong\u003Ered (3+)\u003C/strong\u003E cell means that many campaigns are live for the same people on the same days.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EStart with the three numbers at the top: \u003Cstrong\u003E7 of 15\u003C/strong\u003E region and audience pairs are getting competing offers, and the busiest one, North America · Business Travelers, has \u003Cstrong\u003E3\u003C/strong\u003E campaigns live at once, peaking \u003Cstrong\u003ENov 15 – Nov 28\u003C/strong\u003E. The caption under it reads \u003Cem\u003E2 teams: Demand Gen, Loyalty + 1 unassigned\u003C/em\u003E. Now hover over one of the red cells in the top row: Demand Gen and Loyalty are both aimed at the same business travelers, and so is \u003Cem\u003EAmex Travel Partner Promo\u003C/em\u003E, a CRM campaign with no owner team. This isn't a one-off; it's a planning problem.\u003C/p\u003E\n","\u003Cp\u003EUse the \u003Cstrong\u003ERegion\u003C/strong\u003E filter to see one region's view: everything on the page, including the numbers at the top, follows it. Pick \u003Cstrong\u003EEMEA\u003C/strong\u003E, and you'll see \u003Cstrong\u003E1 of 4\u003C/strong\u003E EMEA pairs with competing offers. Turn on \u003Cstrong\u003EShow all audiences\u003C/strong\u003E to see the pairs that have no overlaps. Use \u003Cstrong\u003EInspect an audience\u003C/strong\u003E below the heatmap to see every campaign for one row, with its owner, dates, and budget.\u003C/p\u003E\n","\u003Ch3\u003ESTEP 5 — Put a dollar value on it\u003C/h3\u003E\n","\u003Cp\u003EThe heatmap shows \u003Cem\u003Ewhere\u003C/em\u003E the plan collides. Leadership will ask \u003Cem\u003Ehow much is at stake\u003C/em\u003E. Ask CoCo to bring in the collisions table. With \u003Ccode\u003Estreamlit_app.py\u003C/code\u003E open, send this prompt:\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Update this app to also load MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS. Below the title, add a red banner showing the number of collisions and their combined budget for the selected region. Below the heatmap, add a table of the collisions sorted by overlap start, with campaign A, campaign B, region, audience, overlap start, overlap end, and combined budget."\u003C/em\u003E\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EReview the changes CoCo proposes, accept them, and click \u003Cstrong\u003ERun\u003C/strong\u003E again. You should see:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EA red banner reading \u003Cstrong\u003E9 collisions\u003C/strong\u003E and \u003Cstrong\u003E$557,500\u003C/strong\u003E in combined budget with \u003Cstrong\u003EAll regions\u003C/strong\u003E selected, and \u003Cstrong\u003E1 collision\u003C/strong\u003E and \u003Cstrong\u003E$63,000\u003C/strong\u003E for \u003Cstrong\u003EEMEA\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EA collisions table with \u003Cstrong\u003E9\u003C/strong\u003E rows, starting with the two that begin on \u003Cstrong\u003ENovember 9\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003E5\u003C/strong\u003E of the 9 collisions starting in November, matching the cluster of orange and red cells on the left side of the heatmap\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/heatmapcollisions.png?v=ce00a69e\" alt=\"heatmapcollisions\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EWant to share it?\u003C/strong\u003E Click \u003Cstrong\u003EDeploy\u003C/strong\u003E in the Workspace to publish the app to \u003Ccode\u003EMERIDIAN_STAY.ANALYTICS\u003C/code\u003E so teammates with access can open it from \u003Cstrong\u003EProjects » Streamlit\u003C/strong\u003E. This step is optional for the lab.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EAsk It With CoWork\u003C/h2\u003E\n","\u003Cp\u003EDuration: 18\u003C/p\u003E\n","\u003Cp\u003EThe data is clean and the heatmap is live. Now make it available to everyone, in plain language. You'll create a \u003Cstrong\u003ESemantic View\u003C/strong\u003E with CoCo, a \u003Cstrong\u003ECortex Agent\u003C/strong\u003E backed by it, and investigate the plan in \u003Cstrong\u003ESnowflake CoWork\u003C/strong\u003E. This happens in the Snowsight UI; no SQL is required.\u003C/p\u003E\n","\u003Ch3\u003ESTEP 6 — Create the Semantic View with CoCo\u003C/h3\u003E\n","\u003Cp\u003EA Semantic View describes your data in \u003Cstrong\u003Ebusiness terms\u003C/strong\u003E: which columns are dimensions (things you filter and group by, like region or channel), which are facts (raw values, like budget), and which words people use for them (\u003Cem\u003E"territory"\u003C/em\u003E means region, \u003Cem\u003E"segment"\u003C/em\u003E means audience). It's the bridge that lets Cortex Analyst turn a question like \u003Cem\u003E"What's launching in APAC in January?"\u003C/em\u003E into correct SQL.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn Snowsight, navigate to \u003Cstrong\u003EAI & ML → Analyst\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003ECreate in Workspaces\u003C/strong\u003E in the top right.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/analyst.png?v=ce00a69e\" alt=\"analyst\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ECreate with CoCo\u003C/strong\u003E. Snowsight opens a new \u003Ccode\u003E.sv.yaml\u003C/code\u003E file, and the CoCo panel asks for a name, a location, and the source tables.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/createwithcoco.png?v=ce00a69e\" alt=\"createwithcoco\"\u003E\u003C/p\u003E\n\u003Col start=\"4\"\u003E\u003Cli\u003ESend CoCo this prompt:\u003C/li\u003E\u003C/ol\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Create the semantic view with these details:\u003C/em\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cem\u003EName: CAMPAIGN_PLANNING_SV\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003ELocation: MERIDIAN_STAY.ANALYTICS\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003ESource tables: MERIDIAN_STAY.CURATED.CAMPAIGNS and MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EUse campaign_id as the unique key for CAMPAIGNS, and add clear descriptions and synonyms for region, audience, and channel\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EMake BUDGET_USD a fact on CAMPAIGNS, and make COMBINED_BUDGET_USD and OVERLAP_DAYS facts on CAMPAIGN_COLLISIONS\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EMake START_DATE and END_DATE time dimensions on CAMPAIGNS, and OVERLAP_START and OVERLAP_END time dimensions on CAMPAIGN_COLLISIONS\u003C/em\u003E\u003C/li\u003E\u003Cli\u003E\u003Cem\u003EAdd this verified query for "Which campaigns collide, and how much combined budget is involved?": SELECT campaign_a_name, campaign_b_name, region, audience, overlap_start, overlap_end, combined_budget_usd FROM MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS ORDER BY overlap_start"\u003C/em\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/blockquote\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003E\n","\u003Cp\u003EAllow CoCo to create the Semantic View draft in the Workspace. This creates an editable draft; it does not publish the view yet.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EReview the draft in the Semantic View editor, one table at a time. Confirm it contains:\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Ccode\u003ECAMPAIGNS\u003C/code\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ccode\u003ECAMPAIGN_ID\u003C/code\u003E as the unique key\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EFacts:\u003C/strong\u003E \u003Ccode\u003EBUDGET_USD\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ETime Dimensions:\u003C/strong\u003E \u003Ccode\u003ESTART_DATE\u003C/code\u003E and \u003Ccode\u003EEND_DATE\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ESynonyms:\u003C/strong\u003E \u003Ccode\u003EREGION\u003C/code\u003E (\u003Cem\u003Egeography, market, territory\u003C/em\u003E), \u003Ccode\u003EAUDIENCE\u003C/code\u003E (\u003Cem\u003Esegment, target group\u003C/em\u003E), and \u003Ccode\u003ECHANNEL\u003C/code\u003E (\u003Cem\u003Emedium, platform\u003C/em\u003E)\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/campaignid.png?v=ce00a69e\" alt=\"campaignid\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003E\u003Ccode\u003ECAMPAIGN_COLLISIONS\u003C/code\u003E\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EFacts:\u003C/strong\u003E \u003Ccode\u003ECOMBINED_BUDGET_USD\u003C/code\u003E and \u003Ccode\u003EOVERLAP_DAYS\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ETime Dimensions:\u003C/strong\u003E \u003Ccode\u003EOVERLAP_START\u003C/code\u003E and \u003Ccode\u003EOVERLAP_END\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ESynonyms:\u003C/strong\u003E \u003Ccode\u003EREGION\u003C/code\u003E (\u003Cem\u003Egeography, market, territory\u003C/em\u003E) and \u003Ccode\u003EAUDIENCE\u003C/code\u003E (\u003Cem\u003Esegment, target group\u003C/em\u003E)\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cstrong\u003EVerified queries\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EOne verified query: \u003Cem\u003E"Which campaigns collide, and how much combined budget is involved?"\u003C/em\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003ECoCo may also add metrics, such as a total budget, or extra synonyms. That's fine. If one of the items above differs, for example \u003Ccode\u003EOVERLAP_DAYS\u003C/code\u003E landing under \u003Cstrong\u003EDimensions\u003C/strong\u003E, ask CoCo to fix it (\u003Cem\u003E"Make OVERLAP_DAYS a fact"\u003C/em\u003E) before publishing.\u003C/p\u003E\n\u003Col start=\"7\"\u003E\u003Cli\u003EClick \u003Cstrong\u003EPublish\u003C/strong\u003E in the top right of the editor. In the dialog, confirm \u003Cstrong\u003EName\u003C/strong\u003E \u003Ccode\u003ECAMPAIGN_PLANNING_SV\u003C/code\u003E, \u003Cstrong\u003EDatabase\u003C/strong\u003E \u003Ccode\u003EMERIDIAN_STAY\u003C/code\u003E, and \u003Cstrong\u003ESchema\u003C/strong\u003E \u003Ccode\u003EANALYTICS\u003C/code\u003E, then click \u003Cstrong\u003EPublish\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/publishsv.png?v=ce00a69e\" alt=\"publishsv\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EPrefer to click through it yourself?\u003C/strong\u003E Choose \u003Cstrong\u003EGuided wizard\u003C/strong\u003E in step 3 instead, select both \u003Ccode\u003ECURATED\u003C/code\u003E tables and all columns, name it \u003Ccode\u003ECAMPAIGN_PLANNING_SV\u003C/code\u003E in \u003Ccode\u003EMERIDIAN_STAY.ANALYTICS\u003C/code\u003E, and click \u003Cstrong\u003EPublish\u003C/strong\u003E.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ESTEP 7 — Create the Cortex Agent\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECortex Analyst\u003C/strong\u003E is Snowflake's text-to-SQL engine; it reads the Semantic View to understand your data. The \u003Cstrong\u003ECortex Agent\u003C/strong\u003E receives questions, routes them to Cortex Analyst, and writes the answer.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn Snowsight, navigate to \u003Cstrong\u003EAI & ML → Agent Studio\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003ECreate agent\u003C/strong\u003E in the top right.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/createagent.png?v=ce00a69e\" alt=\"createagent\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003E\n","\u003Cp\u003EConfigure:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EDatabase and schema:\u003C/strong\u003E \u003Ccode\u003EMERIDIAN_STAY.ANALYTICS\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAgent object name:\u003C/strong\u003E \u003Ccode\u003ECAMPAIGN_PLANNING_AGENT\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003ECreate\u003C/strong\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/agentconfig.png?v=ce00a69e\" alt=\"agentconfig\"\u003E\u003C/p\u003E\n\u003Col start=\"5\"\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003EConfiguration\u003C/strong\u003E near the top of the agent editor.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EUnder the \u003Cstrong\u003EGeneral\u003C/strong\u003E tab, set:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EDescription:\u003C/strong\u003E \u003Ccode\u003EI am the Meridian Stay Campaign Planning Agent. I answer questions about planned marketing campaigns across every channel, region, and audience, and I flag campaigns that target the same audience at the same time.\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EExample questions:\u003C/strong\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ccode\u003EWhich campaigns collide over the same audience between November 2026 and January 2027, and how much combined budget is involved?\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Ccode\u003EWhich collisions are happening in November 2026?\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Ccode\u003EWhat's launching in APAC in January 2027?\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/General.png?v=ce00a69e\" alt=\"General\"\u003E\u003C/p\u003E\n\u003Col start=\"7\"\u003E\u003Cli\u003EUnder the \u003Cstrong\u003EInstructions\u003C/strong\u003E tab, set:\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EOrchestration instructions:\u003C/strong\u003E \u003Ccode\u003EWhenever you can answer visually with a chart, always choose to generate a chart even if the user didn't ask for one.\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EResponse instructions:\u003C/strong\u003E \u003Ccode\u003EGive concise, accurate answers for marketing planners. Name campaigns explicitly and include dates, budgets, and owner teams when relevant.\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/instructions.png?v=ce00a69e\" alt=\"instructions\"\u003E\u003C/p\u003E\n\u003Col start=\"8\"\u003E\u003Cli\u003EClick \u003Cstrong\u003ETools → Add semantic view\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/addsv.png?v=ce00a69e\" alt=\"addsv\"\u003E\u003C/p\u003E\n\u003Col start=\"9\"\u003E\u003Cli\u003E\n","\u003Cp\u003EConfigure the tool:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EService database & schema:\u003C/strong\u003E \u003Ccode\u003EMERIDIAN_STAY.ANALYTICS\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ESelect semantic view:\u003C/strong\u003E \u003Ccode\u003ECAMPAIGN_PLANNING_SV\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EName:\u003C/strong\u003E \u003Ccode\u003ECAMPAIGN_PLANNING_ANALYST\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EDescription:\u003C/strong\u003E \u003Ccode\u003EAnswers questions about Meridian Stay's planned campaigns and audience collisions\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003EAdd\u003C/strong\u003E, then click \u003Cstrong\u003ESave\u003C/strong\u003E in the top right.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/saveagent.png?v=ce00a69e\" alt=\"saveagent\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ESTEP 8 — Ask the agent the key question\u003C/h3\u003E\n","\u003Cp\u003ESince you created the agent through the UI, it's already available in Snowflake CoWork.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn Snowsight, navigate to \u003Cstrong\u003EAI & ML → Snowflake CoWork\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/cowork.png?v=ce00a69e\" alt=\"cowork\"\u003E\u003C/p\u003E\n\u003Col start=\"2\"\u003E\u003Cli\u003ESelect \u003Cstrong\u003ECAMPAIGN_PLANNING_AGENT\u003C/strong\u003E from the agent list.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/planningagent.png?v=ce00a69e\" alt=\"planningagent\"\u003E\u003C/p\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003E\n","\u003Cp\u003EAsk:\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cem\u003E"Which campaigns collide over the same audience between November 2026 and January 2027, and how much combined budget is involved?"\u003C/em\u003E\u003C/p\u003E\n\u003C/blockquote\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe agent should list \u003Cstrong\u003E9 collisions\u003C/strong\u003E with a combined budget of \u003Cstrong\u003E$557,500\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/questionone.png?v=ce00a69e\" alt=\"questionone\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EInvestigate in CoWork\u003C/h3\u003E\n","\u003Cp\u003EThe first answer tells you \u003Cem\u003Ethat\u003C/em\u003E there's a problem. Continue the same conversation to find out \u003Cem\u003Ewhere\u003C/em\u003E to act, the way a planner would:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EFocus on this month.\u003C/strong\u003E Ask: \u003Cem\u003E"Which of those collisions are in November 2026? Chart them by region and audience."\u003C/em\u003E\u003C/p\u003E\n","\u003Cp\u003EYou should see \u003Cstrong\u003E5\u003C/strong\u003E November collisions, and \u003Cstrong\u003ENorth America · Business Travelers\u003C/strong\u003E stands out with \u003Cstrong\u003E3\u003C/strong\u003E of them.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ELook inside the pile-up.\u003C/strong\u003E Ask: \u003Cem\u003E"For North America business travelers in November 2026, list each campaign's channel, dates, budget, and owner team."\u003C/em\u003E\u003C/p\u003E\n","\u003Cp\u003EYou should see \u003Cem\u003EBusiness Travel Year-End Push\u003C/em\u003E (Paid Search, Nov 1–30, $80,000, Demand Gen), \u003Cem\u003ERoad Warrior Rewards\u003C/em\u003E (Email, Nov 16–30, $9,000, Loyalty), and \u003Cem\u003EAmex Travel Partner Promo\u003C/em\u003E (Email, Nov 9–23, $0). The Amex promo only exists in the CRM, so it has no owner team. That's a real finding: a partner campaign nobody on the marketing side owns.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECheck the repeat offender.\u003C/strong\u003E Ask: \u003Cem\u003E"Do the Loyalty Double Points Month and Black Friday Mega Sale campaigns overlap? For how many days, and what's the combined budget?"\u003C/em\u003E\u003C/p\u003E\n","\u003Cp\u003EThey overlap for \u003Cstrong\u003E11 days\u003C/strong\u003E (Nov 20–30) with \u003Cstrong\u003E$97,000\u003C/strong\u003E combined, so last year's Black Friday problem is set to repeat.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ELook ahead.\u003C/strong\u003E Ask: \u003Cem\u003E"What's launching in APAC in January 2027?"\u003C/em\u003E\u003C/p\u003E\n","\u003Cp\u003EYou should see \u003Cem\u003ETokyo Cherry Blossom Preview\u003C/em\u003E, \u003Cem\u003ESydney Summer Kickoff\u003C/em\u003E, and the draft \u003Cem\u003ETokyo Business District Launch\u003C/em\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETurn it into action.\u003C/strong\u003E Ask: \u003Cem\u003E"Draft a short Slack message to the North America Demand Gen and Loyalty teams explaining the November business-traveler overlap and suggesting how to stagger the three campaigns."\u003C/em\u003E\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYour results may vary in wording and chart choice. Before acting on an answer, review the SQL and the rows behind it, especially for totals and date ranges.\u003C/p\u003E\n","\u003Ch3\u003EWhat CoWork adds\u003C/h3\u003E\n","\u003Cp\u003EThe notebook produced clean, open Iceberg tables. The Semantic View gives them business meaning and the words your team actually uses. The Cortex Agent makes that model available in CoWork, where anyone on the team can go from \u003Cem\u003E"is there a problem?"\u003C/em\u003E to \u003Cem\u003E"who needs to talk to whom this week?"\u003C/em\u003E without writing a query or waiting on a report.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ETeardown\u003C/h2\u003E\n","\u003Cp\u003EDuration: 1\u003C/p\u003E\n","\u003Cp\u003EOnce you've finished the lab, run the \u003Cstrong\u003E\u003Ccode\u003Eteardown\u003C/code\u003E\u003C/strong\u003E cell in the notebook, or execute the following in a SQL worksheet:\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBefore running teardown:\u003C/strong\u003E If you're running this guide as part of an Expedition workshop, make sure to run the autograder and answer key before running the teardown. The autograder checks for objects created during this lab, so dropping the database beforehand will cause it to fail.\u003C/p\u003E\n\u003C/blockquote\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE ACCOUNTADMIN;\n\n-- Drops all schemas, Iceberg tables, the stage, the semantic view, and the Cortex Agent\nDROP DATABASE IF EXISTS MERIDIAN_STAY;\n\n-- Removes the Git API integration created for the workspace\nDROP API INTEGRATION IF EXISTS GITHUB_MERIDIAN_LAB;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E Dropping \u003Ccode\u003EMERIDIAN_STAY\u003C/code\u003E cascades to everything inside it. If you deployed the heatmap app to \u003Ccode\u003EMERIDIAN_STAY.ANALYTICS\u003C/code\u003E, it's removed too.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Cp\u003EDuration: 1\u003C/p\u003E\n","\u003Cp\u003ECongratulations! You took Meridian Stay's holiday campaign plan from three disconnected exports to a shared collision heatmap and an agent anyone can ask, prompting CoCo along the way.\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003ELanded raw exports in \u003Cstrong\u003ESnowflake-managed Apache Iceberg tables\u003C/strong\u003E, keeping the data in an open format\u003C/li\u003E\u003Cli\u003EUsed \u003Cstrong\u003ECoCo\u003C/strong\u003E to standardize labels, parse three date formats and text budgets, remove cross-system duplicates, and drop cancelled campaigns\u003C/li\u003E\u003Cli\u003EFound \u003Cstrong\u003E9 audience collisions\u003C/strong\u003E worth \u003Cstrong\u003E$557,500\u003C/strong\u003E in combined budget, including a three-way North America business-traveler pile-up and a repeat of last year's Black Friday overlap\u003C/li\u003E\u003Cli\u003ERan a \u003Cstrong\u003EStreamlit\u003C/strong\u003E collision heatmap and used CoCo to add the collisions and their combined budget\u003C/li\u003E\u003Cli\u003ECreated a \u003Cstrong\u003ESemantic View\u003C/strong\u003E with CoCo and a \u003Cstrong\u003ECortex Agent\u003C/strong\u003E backed by it\u003C/li\u003E\u003Cli\u003EInvestigated the plan in plain language in \u003Cstrong\u003ESnowflake CoWork\u003C/strong\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ERelated Resources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/tables-iceberg\"\u003EApache Iceberg™ tables in Snowflake\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces-git\"\u003EGit-backed Workspaces documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/streamlit/streamlit-in-workspaces/streamlit-in-workspaces-overview\"\u003EStreamlit in Snowflake in Workspaces\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/views-semantic/sql\"\u003ESemantic Views documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-manage\"\u003ECortex Agents documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork/getting-started\"\u003ESnowflake CoWork documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/\"\u003ESnowflake Documentation\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Campaign Planning, Simplified: Build It with CoCo, Ask It with CoWork","elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\u003C!-- ------------------------ --\u003E\n## Overview\nDuration: 2\n\nCampaign data comes from everywhere: ad platforms, the email & SMS platform, the CRM. Each system has its own names for channels, regions, and audiences, its own date format, and its own copy of the biggest campaigns. So nobody has a single, trustworthy view of what's launching, and teams end up hitting the same audience with competing offers in the same week.\n\nIn this hands-on lab you'll fix that for **Meridian Stay**, a fictional global hotel brand, just as its holiday season plan is going live. You'll land the raw campaign exports in open **Apache Iceberg** tables, use **Snowflake CoCo** to clean and standardize them, and surface every audience collision on a live collision heatmap. Then you'll hand the result to the whole team through **Snowflake CoWork**, so anyone can ask *\"What's launching in APAC next month?\"* and get an answer in seconds.\n\n### Prerequisites\n- No coding experience required. CoCo writes the SQL; you describe what you want and review the result.\n\n### What You'll Learn\n- How to clone a public GitHub repo as a Git-backed Snowflake Workspace and run a notebook inside it\n- How to land raw data in **Snowflake-managed Apache Iceberg tables**, an open format that other engines can read\n- How to use **CoCo** to standardize labels, parse dates and budgets, remove duplicates, and filter out cancelled campaigns\n- How to find audience collisions across teams and channels\n- How to run and customize a **Streamlit** collision heatmap with CoCo\n- How to create a **Semantic View** with CoCo and a **Cortex Agent** backed by it\n- How to investigate business questions in plain language in **Snowflake CoWork**\n\n### What You'll Need\n- A free Snowflake trial account: [https://signup.snowflake.com/](https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&trial=student&cloud=aws&region=us-east-2&utm_campaign=introtosnowflake&utm_cta=developer-guides)\n- The companion GitHub repo: [https://github.com/Snowflake-Labs/expedition-2026-day-2-hol](https://github.com/Snowflake-Labs/expedition-2026-day-2-hol)\n\n### What You'll Build\n- A governed, deduplicated campaign list built from three messy exports, stored as Iceberg\n- A table of every audience collision in Meridian Stay's November 2026 – January 2027 plan\n- A live collision heatmap app\n- A Cortex Agent that answers campaign-planning questions in Snowflake CoWork\n\n\u003C!-- ------------------------ --\u003E\n## Open a Snowflake Trial Account\nDuration: 3\n\nTo complete this lab, you'll need a Snowflake account. A free Snowflake trial account works well. To open one:\n\n1. Navigate to [https://signup.snowflake.com/](https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&trial=student&cloud=aws&region=us-east-2&utm_campaign=introtosnowflake&utm_cta=developer-guides). This link pre-selects **AWS** and the **US East (Ohio)** region for you.\n\n2. Complete the first page of the form.\n\n3. On the next section, set the Snowflake edition to **Enterprise (Most popular)**.\n\n4. Confirm **AWS – Amazon Web Services** is selected as the cloud provider (pre-filled by the link).\n\n5. Confirm **US East (Ohio)** is selected as the region (pre-filled by the link).\n\n6. Complete the rest of the form and click **Get started**.\n\n\u003C!-- ------------------------ --\u003E\n## Understand the Scenario\nDuration: 2\n\nYou're on the marketing operations team at Meridian Stay, and it's November 2026. Last year, the Loyalty team and Brand Marketing both targeted rewards members with competing Black Friday offers, and nobody noticed until the emails went out. Leadership wants to know: is it about to happen again?\n\nThe root cause is simple: campaign plans live in three systems that don't agree with each other.\n\n| Source system | Export | How it's messy |\n|---|---|---|\n| Ad platforms | `paid_media_export.csv` | Channel codes like `fb_ads` and `google_ads`, region `NA`, budgets stored as text (`\"$65,000\"`), and two rows exported twice |\n| Email & SMS platform (e.g., Marketo, HubSpot, Braze) | `email_sms_export.csv` | `MM/DD/YYYY` dates, regions like `US & Canada`, segments like `Corporate Segment` |\n| CRM | `crm_campaigns_export.csv` | `Nov 02, 2026` dates, copies of the biggest paid campaigns (one with a trailing space, one in ALL CAPS), and a **cancelled** campaign, *Veterans Day Weekend Blitz*, that was never removed |\n\n### Here's the plan\n\n1. **Land** the three exports, exactly as they arrived, in **Apache Iceberg** tables.\n2. **Clean** them with CoCo into one governed campaign list, also stored as Iceberg.\n3. **Find** every audience collision: two campaigns aimed at the same audience in the same region on overlapping dates.\n4. **See** where collisions cluster on a live heatmap and put a dollar value on them.\n5. **Ask** planning questions in plain language through a Cortex Agent in **Snowflake CoWork**.\n\nEverything through step 4 runs from a **single notebook** (`lab.ipynb`) and a pre-built app in the companion repo. Step 5 is done in the Snowsight UI. Let's get started!\n\n\u003C!-- ------------------------ --\u003E\n## Set Up Your Workspace\nDuration: 5\n\nThere are no setup scripts to run and no SQL worksheets to open first. Your first action is to create a **Git-backed Workspace** that clones the companion repo. The repo contains the notebook you'll run (`lab.ipynb`), the three campaign exports (`data/`), and the collision heatmap app (`campaign_timeline/`).\n\n### Sign in as ACCOUNTADMIN\n\nMake sure you are signed into your trial account. Confirm your active role is **ACCOUNTADMIN**: click your name in the bottom-left corner of Snowsight to see the active role. If it shows a different role, choose **Switch role** → **ACCOUNTADMIN**.\n\n![role](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/role.png?v=ce00a69e)\n\n### Create a Git-backed Workspace\n\n1. In Snowsight, navigate to **Projects » Workspaces**.\n\n2. Click the **+** icon next to **Workspaces/Databases** → **Create new Git workspace**.\n\n![gitworkspace](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/gitworkspace.png?v=ce00a69e)\n\n3. Fill out the modal:\n   - **Repository URL:** `https://github.com/Snowflake-Labs/expedition-2026-day-2-hol`\n   - **Workspace name:** anything you like (e.g., `campaign-planning`)\n   - **API integration:** click **+ / Create new** and provide:\n     - **Name:** `GITHUB_MERIDIAN_LAB`\n     - **Allowed prefixes:** `https://github.com/Snowflake-Labs`\n   - Check **Public repository**.\n\n![gitrepository](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/gitrepository.png?v=ce00a69e)\n![apiintegration](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/apiintegration.png?v=ce00a69e)\n\n4. Click **Create**.\n\n\u003E **What just happened?** The Workspace modal created a Git API integration for you, a one-time step that tells Snowflake which GitHub organization is an allowed source for Git-backed Workspaces.\n\nThe Workspace opens with the repo's files visible in the file explorer on the left.\n\n### Open the notebook and set its compute\n\n1. In the Workspace file explorer, open **`lab.ipynb`**.\n\n2. Click **Connect** next to the Run button and select **Create and connect**. Wait for the status bar at the bottom of the notebook to show **Connected** before proceeding.\n\n![connected](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/connected.png?v=ce00a69e)\n\n3. Set the notebook's active **role** and **warehouse** using the **role & warehouse picker** at the top of the Notebooks editor:\n   - **Role:** **ACCOUNTADMIN**\n   - **Warehouse:** **COMPUTE_WH** (the default warehouse in every trial account)\n\n4. Work top-to-bottom through the notebook. Markdown cells explain each step; code cells contain the SQL, some of which you'll generate yourself with CoCo. Run a cell with **▶** (or **Shift+Enter**).\n\n\u003E Throughout the lab, the notebook shows a **CoCo prompt** in the markdown cell directly above each empty SQL cell. You can use the prompts from there or copy them from this guide. They should be identical or similar.\n\n### Open the CoCo panel\n\nOpen the **CoCo** chat panel from the Workspace toolbar. You'll send it prompts throughout the lab.\n\n![coco](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/coco.png?v=ce00a69e)\n\n\u003E **Key principle:** Use CoCo to generate the hard parts and understand why. The workflow is: describe → generate → compare → run. After CoCo generates SQL, compare it against the **Expected output** shown in the notebook. If they match, click **Allow** to run it. Optionally, copy the SQL into the notebook cell for future reference.\n\n### Run the setup cell\n\nThe first SQL cell in the notebook (**`setup`**) creates the `MERIDIAN_STAY` database with three schemas:\n\n- `RAW`: the exports, exactly as they arrived\n- `CURATED`: clean, governed tables\n- `ANALYTICS`: the semantic view and agent\n\nIt also grants the Cortex Agent privileges your role needs later. Run the **`setup`** cell before continuing. You should see *\"Statement executed successfully.\"*\n\n![setupcell](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/setupcell.png?v=ce00a69e)\n\n\u003C!-- ------------------------ --\u003E\n## Land Raw Exports\nDuration: 7\n\nThe first step is to get the raw exports into Snowflake **without changing them**, so you always have the original to compare against.\n\n### Why Apache Iceberg?\n\n**Apache Iceberg** is an open table format. An Iceberg table's data is stored as Parquet files plus open metadata, so other engines (Spark, Trino, DuckDB, and more) can read the same tables through Snowflake Horizon Catalog. Your campaign data stays open instead of being locked into one tool, which matters when the data science team, an agency, or a partner platform needs it too.\n\nIn this lab you'll use **Snowflake-managed Iceberg tables** (`CATALOG = 'SNOWFLAKE'` and `EXTERNAL_VOLUME = 'SNOWFLAKE_MANAGED'`). Snowflake manages the storage for you, so there's no cloud bucket or IAM setup.\n\n### Create the raw tables\n\nRun the **`raw_tables`** cell. It creates:\n\n- Three raw Iceberg tables, one per export, with every column as `STRING` (exactly as exported)\n- A CSV file format, `RAW.CSV_FF`\n- An internal stage, `RAW.CAMPAIGN_EXPORTS`, to hold the files\n\n### Upload the export files\n\nRun the **`upload_files`** Python cell. It copies the three CSVs from the repo's `data/` folder into the stage. You should see three files with status `UPLOADED`.\n\n### STEP 1 — Load the exports\n\n`COPY INTO` is Snowflake's bulk-loading command. It reads files from a stage and inserts them into a table, and it works the same way whether the target is a standard table or an Iceberg table.\n\nSend this prompt to CoCo. Compare the output against the expected output in the notebook. If they match, click **Allow** to run it.\n\n\u003E *\"Load the three CSV files in the stage @MERIDIAN_STAY.RAW.CAMPAIGN_EXPORTS into their matching Iceberg tables in MERIDIAN_STAY.RAW: paid_media_export.csv into PAID_MEDIA_EXPORT, email_sms_export.csv into EMAIL_SMS_EXPORT, and crm_campaigns_export.csv into CRM_CAMPAIGNS_EXPORT. Use the file format MERIDIAN_STAY.RAW.CSV_FF and load the columns in file order.\"*\n\n![firstprompt](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/firstprompt.png?v=ce00a69e)\n\nYou should see **16**, **10**, and **7** rows loaded. If CoCo's first attempt fails and it retries with a corrected statement, that's normal: it reads the error and fixes its own SQL.\n\n\u003E **Seeing `MATCH_BY_COLUMN_NAME = NONE` at the end of each statement?** That's fine. It tells Snowflake to load columns by position, which is the default and exactly what *\"in file order\"* asks for.\n\n### See the mess\n\nRun the **`peek_raw`** cell. It lines up all 33 raw rows from the three exports in one grid, sorted by campaign name so copies of the same campaign sit next to each other. Scroll through and notice:\n\n- *Thanksgiving Getaway Sale* appears **three times**: twice in the ad platform export (a re-export duplicate) and once in the CRM, with a trailing space.\n- *Black Friday Mega Sale* appears twice, once in ALL CAPS.\n- The same channel is `fb_ads` in one system and `Social Media` in another; the same region is `NA`, `US & Canada`, or `N. America`.\n- Three date formats: `2026-11-02`, `11/09/2026`, and `Nov 02, 2026`.\n- Budgets like `\"$65,000\"` are text, not numbers.\n- *Veterans Day Weekend Blitz* has a status of **Cancelled**, but it's still in the list.\n\nYou can't find collisions until all three systems speak the same language, and that's next.\n\n\u003C!-- ------------------------ --\u003E\n## Clean and Standardize With CoCo\nDuration: 12\n\nNow you'll turn three messy exports into one governed campaign list. This usually takes a marketing ops analyst a day of spreadsheet work. With CoCo, you describe the rules in plain language and review the SQL it writes.\n\n### The rules\n\n- **One vocabulary.** Every channel, region, and audience maps to a single standard label.\n- **Real dates and numbers.** Three date formats become real `DATE` values, and `\"$65,000\"` becomes `65000.00`.\n- **No duplicates.** A campaign that appears in more than one system, or twice in the same export, is kept once. The system of record (ad platforms or the email & SMS platform) wins over the CRM copy.\n- **No cancelled campaigns.** A cancelled CRM campaign shouldn't show up on anyone's plan.\n\n### STEP 2 — Let CoCo find the mess\n\nBefore building anything, ask CoCo to compare the three sources. It queries the raw tables itself and shows you how differently each system describes the *same* things.\n\n\u003E *\"Compare how the three tables in MERIDIAN_STAY.RAW label channel, region, and audience. Map every label to one of these standard values:*\n\u003E - *Channel: Paid Social, Paid Search, Display, Email, SMS*\n\u003E - *Region: North America, EMEA, APAC, LATAM, Global*\n\u003E - *Audience: Leisure Travelers, Business Travelers, Families, Loyalty Members, Meeting Planners, Wellness Seekers, All Guests*\n\u003E\n\u003E *Also point out how dates and budgets are formatted differently, and any campaigns whose status means they shouldn't be on the plan.\"*\n\n![secondprompt](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/secondprompt.png?v=ce00a69e)\n\nCoCo should map, for example, `fb_ads`, `paid_social`, and `Social Media` to **Paid Social**, and `NA`, `US & Canada`, and `N. America` to **North America**. It should also call out the three date formats, the text budgets, and the cancelled *Veterans Day Weekend Blitz*. It may mention the **Draft** *Tokyo Business District Launch* too; drafts are still planned, so it stays. The full expected mapping is in the notebook.\n\n\u003E **Why give CoCo the standard values?** They're business decisions, like \"`Corporate Segment` means Business Travelers.\" Listing them is how you make sure CoCo applies *your* team's vocabulary instead of inventing its own.\n\n### STEP 3 — Build the unified CAMPAIGNS table\n\nIn the **same CoCo conversation**, send this prompt. CoCo reuses the mapping from STEP 2 and writes the SQL. Your SQL may not match the expected output in the notebook word for word, and that's fine; the check cell is what tells you it's right. Click **Allow** to run it.\n\n\u003E *\"Using that mapping, create a Snowflake-managed Iceberg table MERIDIAN_STAY.CURATED.CAMPAIGNS (EXTERNAL_VOLUME = 'SNOWFLAKE_MANAGED') that combines the three raw tables into one campaign list:*\n\u003E - *Columns: campaign_id, campaign_name, channel, region, audience, start_date, end_date, budget_usd, owner_team, status, source_system*\n\u003E - *Convert dates and budgets to real dates and numbers*\n\u003E - *Drop cancelled campaigns*\n\u003E - *Remove duplicates with the same name (ignoring case and extra spaces) and dates, keeping the ad platform or email & SMS copy over the CRM copy\"*\n\n### Check the result\n\nRun the **`check_campaigns`** cell. You should see:\n\n| campaigns | unmapped_values | channels | regions | audiences |\n|---|---|---|---|---|\n| 27 | 0 | 5 | 5 | 7 |\n\nThat's 33 raw rows, minus 5 duplicates and 1 cancelled campaign. If your numbers are different, ask CoCo to fix it rather than editing the SQL yourself:\n\n- `unmapped_values` above 0: *\"Which rows in MERIDIAN_STAY.CURATED.CAMPAIGNS have a NULL channel, region, audience, date, or budget? Fix the mapping.\"*\n- More than 27 campaigns: *\"Which campaigns appear more than once in MERIDIAN_STAY.CURATED.CAMPAIGNS? Fix the duplicate removal.\"*\n\nShort on time? Paste the expected output from the notebook into the empty cell and run it.\n\n### Before and after\n\nRun the **`before_after`** cell. It shows the campaigns that needed the most cleaning, as they arrived in `RAW` and as they are now in `CURATED`:\n\n| Layer | Source | Campaign | Channel | Region | Audience | Start date | Budget | Status |\n|---|---|---|---|---|---|---|---|---|\n| Before | CRM_CAMPAIGNS_EXPORT | Thanksgiving Getaway Sale *(trailing space)* | Social Media | N. America | Leisure | Nov 02, 2026 | 65000 | Active |\n| Before | PAID_MEDIA_EXPORT | Thanksgiving Getaway Sale | fb_ads | NA | leisure | 2026-11-02 | $65,000 | |\n| Before | PAID_MEDIA_EXPORT | Thanksgiving Getaway Sale | fb_ads | NA | leisure | 2026-11-02 | $65,000 | |\n| **After** | Paid Media | Thanksgiving Getaway Sale | Paid Social | North America | Leisure Travelers | 2026-11-02 | 65000.00 | Active |\n\nThe same happens for *Black Friday Mega Sale* (two copies become one), and *Veterans Day Weekend Blitz* has no \"after\" row at all. Six messy rows become two clean ones.\n\n![beforeafter](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/beforeafter.png?v=ce00a69e)\n\n### STEP 4 — Find every audience collision\n\nA **collision** is two different campaigns that target the same audience, in the same region, on overlapping dates. That's exactly what happened with last year's Black Friday offers.\n\nSend this prompt to CoCo. Compare the output against the expected output in the notebook, then click **Allow** to run it. The prompt names the columns so that everyone's table matches the Semantic View and CoWork questions later.\n\n\u003E *\"Create a Snowflake-managed Iceberg table MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS (EXTERNAL_VOLUME = 'SNOWFLAKE_MANAGED') listing every pair of campaigns in CURATED.CAMPAIGNS that target the same region and audience on overlapping dates. List each pair once.*\n\u003E - *Columns: campaign_a_id, campaign_a_name, campaign_b_id, campaign_b_name, region, audience, overlap_start, overlap_end, overlap_days, combined_budget_usd\"*\n\n### Check the result\n\nRun the **`check_collisions`** cell. You should see **9 rows**, with `total_collisions` = **9** and `total_combined_budget` = **$557,500**. If you see 18 rows, each pair is listed twice; ask CoCo to *\"list each pair only once.\"* The collisions are (A and B may be swapped in your table):\n\n| Campaign A | Campaign B | Region | Audience | Overlap starts | Combined budget |\n|---|---|---|---|---|---|\n| Amex Travel Partner Promo | Business Travel Year-End Push | North America | Business Travelers | 2026-11-09 | $80,000 |\n| Autumn Weekend Escapes | Thanksgiving Getaway Sale | North America | Leisure Travelers | 2026-11-09 | $77,000 |\n| Amex Travel Partner Promo | Road Warrior Rewards | North America | Business Travelers | 2026-11-16 | $9,000 |\n| Road Warrior Rewards | Business Travel Year-End Push | North America | Business Travelers | 2026-11-16 | $89,000 |\n| Loyalty Double Points Month | Black Friday Mega Sale | North America | Loyalty Members | 2026-11-20 | $97,000 |\n| EMEA Winter Sun | London Festive Stays | EMEA | Leisure Travelers | 2026-12-01 | $63,000 |\n| Holiday Gift Card Push | Holiday Family Getaways | North America | Families | 2026-12-05 | $47,500 |\n| APAC Year-End Flash Sale | Singapore Staycation Deals | APAC | Families | 2026-12-20 | $40,000 |\n| Tokyo Cherry Blossom Preview | Sydney Summer Kickoff | APAC | Leisure Travelers | 2027-01-10 | $55,000 |\n\nFive of the nine are in **November**, including the answer to leadership's question: *Loyalty Double Points Month* and *Black Friday Mega Sale* are about to hit rewards members at the same time, again.\n\nNotice what's *not* on the list: the cancelled *Veterans Day Weekend Blitz*. Without the clean-up step, it would have raised two false alarms against *Thanksgiving Getaway Sale* and *Autumn Weekend Escapes*.\n\n\u003C!-- ------------------------ --\u003E\n## See Where Collisions Cluster\nDuration: 9\n\nA table of collisions is useful. A view the whole team can scan in five seconds is better. The companion repo includes a pre-built **Streamlit** app that turns `CURATED.CAMPAIGNS` into a **collision heatmap** for the whole holiday season.\n\n### Run the heatmap\n\n1. In the Workspace file explorer, open **`campaign_timeline/streamlit_app.py`**.\n\n![streamlitapp](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/streamlitapp.png?v=ce00a69e)\n\n2. If a banner says *\"This file looks like a Streamlit app, but is missing configuration\"*, click **Convert to streamlit app**. The Workspace adds the configuration files the app needs.\n\n![convert](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/convert.png?v=ce00a69e)\n\n3. Click **Run**. The app runs privately for you on a container runtime and reads straight from `MERIDIAN_STAY.CURATED.CAMPAIGNS`.\n\n![heatmap](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/heatmap.png?v=ce00a69e)\n\n### How to read it\n\n- Each **row** is a region and audience pair, like *North America · Business Travelers*. The app opens on only the pairs with competing offers, hottest at the top.\n- Each **column** is a week, from November 2026 through January 2027.\n- A **grey** cell means one campaign is reaching that audience that week, which is fine. An **orange (2)** or **red (3+)** cell means that many campaigns are live for the same people on the same days.\n\nStart with the three numbers at the top: **7 of 15** region and audience pairs are getting competing offers, and the busiest one, North America · Business Travelers, has **3** campaigns live at once, peaking **Nov 15 – Nov 28**. The caption under it reads *2 teams: Demand Gen, Loyalty + 1 unassigned*. Now hover over one of the red cells in the top row: Demand Gen and Loyalty are both aimed at the same business travelers, and so is *Amex Travel Partner Promo*, a CRM campaign with no owner team. This isn't a one-off; it's a planning problem.\n\nUse the **Region** filter to see one region's view: everything on the page, including the numbers at the top, follows it. Pick **EMEA**, and you'll see **1 of 4** EMEA pairs with competing offers. Turn on **Show all audiences** to see the pairs that have no overlaps. Use **Inspect an audience** below the heatmap to see every campaign for one row, with its owner, dates, and budget.\n\n### STEP 5 — Put a dollar value on it\n\nThe heatmap shows *where* the plan collides. Leadership will ask *how much is at stake*. Ask CoCo to bring in the collisions table. With `streamlit_app.py` open, send this prompt:\n\n\u003E *\"Update this app to also load MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS. Below the title, add a red banner showing the number of collisions and their combined budget for the selected region. Below the heatmap, add a table of the collisions sorted by overlap start, with campaign A, campaign B, region, audience, overlap start, overlap end, and combined budget.\"*\n\nReview the changes CoCo proposes, accept them, and click **Run** again. You should see:\n\n- A red banner reading **9 collisions** and **$557,500** in combined budget with **All regions** selected, and **1 collision** and **$63,000** for **EMEA**\n- A collisions table with **9** rows, starting with the two that begin on **November 9**\n- **5** of the 9 collisions starting in November, matching the cluster of orange and red cells on the left side of the heatmap\n\n![heatmapcollisions](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/heatmapcollisions.png?v=ce00a69e)\n\n\u003E **Want to share it?** Click **Deploy** in the Workspace to publish the app to `MERIDIAN_STAY.ANALYTICS` so teammates with access can open it from **Projects » Streamlit**. This step is optional for the lab.\n\n\u003C!-- ------------------------ --\u003E\n## Ask It With CoWork\nDuration: 18\n\nThe data is clean and the heatmap is live. Now make it available to everyone, in plain language. You'll create a **Semantic View** with CoCo, a **Cortex Agent** backed by it, and investigate the plan in **Snowflake CoWork**. This happens in the Snowsight UI; no SQL is required.\n\n### STEP 6 — Create the Semantic View with CoCo\n\nA Semantic View describes your data in **business terms**: which columns are dimensions (things you filter and group by, like region or channel), which are facts (raw values, like budget), and which words people use for them (*\"territory\"* means region, *\"segment\"* means audience). It's the bridge that lets Cortex Analyst turn a question like *\"What's launching in APAC in January?\"* into correct SQL.\n\n1. In Snowsight, navigate to **AI & ML → Analyst**.\n\n2. Click **Create in Workspaces** in the top right.\n\n![analyst](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/analyst.png?v=ce00a69e)\n\n3. Click **Create with CoCo**. Snowsight opens a new `.sv.yaml` file, and the CoCo panel asks for a name, a location, and the source tables.\n\n![createwithcoco](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/createwithcoco.png?v=ce00a69e)\n\n4. Send CoCo this prompt:\n\n\u003E *\"Create the semantic view with these details:*\n\u003E - *Name: CAMPAIGN_PLANNING_SV*\n\u003E - *Location: MERIDIAN_STAY.ANALYTICS*\n\u003E - *Source tables: MERIDIAN_STAY.CURATED.CAMPAIGNS and MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS*\n\u003E - *Use campaign_id as the unique key for CAMPAIGNS, and add clear descriptions and synonyms for region, audience, and channel*\n\u003E - *Make BUDGET_USD a fact on CAMPAIGNS, and make COMBINED_BUDGET_USD and OVERLAP_DAYS facts on CAMPAIGN_COLLISIONS*\n\u003E - *Make START_DATE and END_DATE time dimensions on CAMPAIGNS, and OVERLAP_START and OVERLAP_END time dimensions on CAMPAIGN_COLLISIONS*\n\u003E - *Add this verified query for \"Which campaigns collide, and how much combined budget is involved?\": SELECT campaign_a_name, campaign_b_name, region, audience, overlap_start, overlap_end, combined_budget_usd FROM MERIDIAN_STAY.CURATED.CAMPAIGN_COLLISIONS ORDER BY overlap_start\"*\n\n5. Allow CoCo to create the Semantic View draft in the Workspace. This creates an editable draft; it does not publish the view yet.\n\n6. Review the draft in the Semantic View editor, one table at a time. Confirm it contains:\n\n   **`CAMPAIGNS`**\n   - `CAMPAIGN_ID` as the unique key\n   - **Facts:** `BUDGET_USD`\n   - **Time Dimensions:** `START_DATE` and `END_DATE`\n   - **Synonyms:** `REGION` (*geography, market, territory*), `AUDIENCE` (*segment, target group*), and `CHANNEL` (*medium, platform*)\n\n![campaignid](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/campaignid.png?v=ce00a69e)\n\n   **`CAMPAIGN_COLLISIONS`**\n   - **Facts:** `COMBINED_BUDGET_USD` and `OVERLAP_DAYS`\n   - **Time Dimensions:** `OVERLAP_START` and `OVERLAP_END`\n   - **Synonyms:** `REGION` (*geography, market, territory*) and `AUDIENCE` (*segment, target group*)\n\n   **Verified queries**\n   - One verified query: *\"Which campaigns collide, and how much combined budget is involved?\"*\n\n   CoCo may also add metrics, such as a total budget, or extra synonyms. That's fine. If one of the items above differs, for example `OVERLAP_DAYS` landing under **Dimensions**, ask CoCo to fix it (*\"Make OVERLAP_DAYS a fact\"*) before publishing.\n\n7. Click **Publish** in the top right of the editor. In the dialog, confirm **Name** `CAMPAIGN_PLANNING_SV`, **Database** `MERIDIAN_STAY`, and **Schema** `ANALYTICS`, then click **Publish**.\n\n![publishsv](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/publishsv.png?v=ce00a69e)\n\n\u003E **Prefer to click through it yourself?** Choose **Guided wizard** in step 3 instead, select both `CURATED` tables and all columns, name it `CAMPAIGN_PLANNING_SV` in `MERIDIAN_STAY.ANALYTICS`, and click **Publish**.\n\n### STEP 7 — Create the Cortex Agent\n\n**Cortex Analyst** is Snowflake's text-to-SQL engine; it reads the Semantic View to understand your data. The **Cortex Agent** receives questions, routes them to Cortex Analyst, and writes the answer.\n\n1. In Snowsight, navigate to **AI & ML → Agent Studio**.\n\n2. Click **Create agent** in the top right.\n\n![createagent](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/createagent.png?v=ce00a69e)\n\n3. Configure:\n   - **Database and schema:** `MERIDIAN_STAY.ANALYTICS`\n   - **Agent object name:** `CAMPAIGN_PLANNING_AGENT`\n\n4. Click **Create**.\n\n![agentconfig](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/agentconfig.png?v=ce00a69e)\n\n5. Click **Configuration** near the top of the agent editor.\n\n6. Under the **General** tab, set:\n   - **Description:** `I am the Meridian Stay Campaign Planning Agent. I answer questions about planned marketing campaigns across every channel, region, and audience, and I flag campaigns that target the same audience at the same time.`\n   - **Example questions:**\n     - `Which campaigns collide over the same audience between November 2026 and January 2027, and how much combined budget is involved?`\n     - `Which collisions are happening in November 2026?`\n     - `What's launching in APAC in January 2027?`\n\n![General](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/General.png?v=ce00a69e)\n\n7. Under the **Instructions** tab, set:\n   - **Orchestration instructions:** `Whenever you can answer visually with a chart, always choose to generate a chart even if the user didn't ask for one.`\n   - **Response instructions:** `Give concise, accurate answers for marketing planners. Name campaigns explicitly and include dates, budgets, and owner teams when relevant.`\n\n![instructions](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/instructions.png?v=ce00a69e)\n\n8. Click **Tools → Add semantic view**.\n\n![addsv](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/addsv.png?v=ce00a69e)\n\n9. Configure the tool:\n   - **Service database & schema:** `MERIDIAN_STAY.ANALYTICS`\n   - **Select semantic view:** `CAMPAIGN_PLANNING_SV`\n   - **Name:** `CAMPAIGN_PLANNING_ANALYST`\n   - **Description:** `Answers questions about Meridian Stay's planned campaigns and audience collisions`\n\n10. Click **Add**, then click **Save** in the top right.\n\n![saveagent](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/saveagent.png?v=ce00a69e)\n\n### STEP 8 — Ask the agent the key question\n\nSince you created the agent through the UI, it's already available in Snowflake CoWork.\n\n1. In Snowsight, navigate to **AI & ML → Snowflake CoWork**.\n\n![cowork](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/cowork.png?v=ce00a69e)\n\n2. Select **CAMPAIGN_PLANNING_AGENT** from the agent list.\n\n![planningagent](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/planningagent.png?v=ce00a69e)\n\n3. Ask:\n\n   \u003E *\"Which campaigns collide over the same audience between November 2026 and January 2027, and how much combined budget is involved?\"*\n\nThe agent should list **9 collisions** with a combined budget of **$557,500**.\n\n![questionone](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/campaign-planning-with-coco-and-cowork/questionone.png?v=ce00a69e)\n\n### Investigate in CoWork\n\nThe first answer tells you *that* there's a problem. Continue the same conversation to find out *where* to act, the way a planner would:\n\n1. **Focus on this month.** Ask: *\"Which of those collisions are in November 2026? Chart them by region and audience.\"*\n\n   You should see **5** November collisions, and **North America · Business Travelers** stands out with **3** of them.\n\n2. **Look inside the pile-up.** Ask: *\"For North America business travelers in November 2026, list each campaign's channel, dates, budget, and owner team.\"*\n\n   You should see *Business Travel Year-End Push* (Paid Search, Nov 1–30, $80,000, Demand Gen), *Road Warrior Rewards* (Email, Nov 16–30, $9,000, Loyalty), and *Amex Travel Partner Promo* (Email, Nov 9–23, $0). The Amex promo only exists in the CRM, so it has no owner team. That's a real finding: a partner campaign nobody on the marketing side owns.\n\n3. **Check the repeat offender.** Ask: *\"Do the Loyalty Double Points Month and Black Friday Mega Sale campaigns overlap? For how many days, and what's the combined budget?\"*\n\n   They overlap for **11 days** (Nov 20–30) with **$97,000** combined, so last year's Black Friday problem is set to repeat.\n\n4. **Look ahead.** Ask: *\"What's launching in APAC in January 2027?\"*\n\n   You should see *Tokyo Cherry Blossom Preview*, *Sydney Summer Kickoff*, and the draft *Tokyo Business District Launch*.\n\n5. **Turn it into action.** Ask: *\"Draft a short Slack message to the North America Demand Gen and Loyalty teams explaining the November business-traveler overlap and suggesting how to stagger the three campaigns.\"*\n\nYour results may vary in wording and chart choice. Before acting on an answer, review the SQL and the rows behind it, especially for totals and date ranges.\n\n### What CoWork adds\n\nThe notebook produced clean, open Iceberg tables. The Semantic View gives them business meaning and the words your team actually uses. The Cortex Agent makes that model available in CoWork, where anyone on the team can go from *\"is there a problem?\"* to *\"who needs to talk to whom this week?\"* without writing a query or waiting on a report.\n\n\u003C!-- ------------------------ --\u003E\n## Teardown\nDuration: 1\n\nOnce you've finished the lab, run the **`teardown`** cell in the notebook, or execute the following in a SQL worksheet:\n\n\u003E **Before running teardown:** If you're running this guide as part of an Expedition workshop, make sure to run the autograder and answer key before running the teardown. The autograder checks for objects created during this lab, so dropping the database beforehand will cause it to fail.\n\n```sql\nUSE ROLE ACCOUNTADMIN;\n\n-- Drops all schemas, Iceberg tables, the stage, the semantic view, and the Cortex Agent\nDROP DATABASE IF EXISTS MERIDIAN_STAY;\n\n-- Removes the Git API integration created for the workspace\nDROP API INTEGRATION IF EXISTS GITHUB_MERIDIAN_LAB;\n```\n\n\u003E **Note:** Dropping `MERIDIAN_STAY` cascades to everything inside it. If you deployed the heatmap app to `MERIDIAN_STAY.ANALYTICS`, it's removed too.\n\n\u003C!-- ------------------------ --\u003E\n## Conclusion And Resources\nDuration: 1\n\nCongratulations! You took Meridian Stay's holiday campaign plan from three disconnected exports to a shared collision heatmap and an agent anyone can ask, prompting CoCo along the way.\n\n### What You Learned\n\n- Landed raw exports in **Snowflake-managed Apache Iceberg tables**, keeping the data in an open format\n- Used **CoCo** to standardize labels, parse three date formats and text budgets, remove cross-system duplicates, and drop cancelled campaigns\n- Found **9 audience collisions** worth **$557,500** in combined budget, including a three-way North America business-traveler pile-up and a repeat of last year's Black Friday overlap\n- Ran a **Streamlit** collision heatmap and used CoCo to add the collisions and their combined budget\n- Created a **Semantic View** with CoCo and a **Cortex Agent** backed by it\n- Investigated the plan in plain language in **Snowflake CoWork**\n\n### Related Resources\n\n- [Apache Iceberg™ tables in Snowflake](https://docs.snowflake.com/en/user-guide/tables-iceberg)\n- [Git-backed Workspaces documentation](https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces-git)\n- [Streamlit in Snowflake in Workspaces](https://docs.snowflake.com/en/developer-guide/streamlit/streamlit-in-workspaces/streamlit-in-workspaces-overview)\n- [Semantic Views documentation](https://docs.snowflake.com/en/user-guide/views-semantic/sql)\n- [Cortex Agents documentation](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-manage)\n- [Snowflake CoWork documentation](https://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork/getting-started)\n- [Snowflake Documentation](https://docs.snowflake.com/)\n","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],":items":{},":itemsOrder":[],":type":"snowflake-site/components/contentfragment","isDeveloperGuidesPage":false,"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-d0cfac2750","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-da625695b3",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-e8c23e1327","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2026-10-09",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-48063f642a","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake 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