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raises questions right away. Which region is behind? Which segment? Which accounts? On many teams the answers live in exported spreadsheets or static report decks. They go stale as soon as the data changes, and every follow-up question means another export or another request to an analyst.\u003C/p\u003E\n","\u003Cp\u003E\u003Ca href=\"https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards\"\u003ESnowflake Dashboards\u003C/a\u003E (public preview) give the team one shared source of truth that they can also talk to. Analysts build a dashboard by describing it to Cortex Code (CoCo), then share it with the right roles. Anyone with access can open it in Snowflake CoWork and ask it questions: summarize what it shows, explain what drove a change, or narrow it to one segment. The answers come from the same governed data the charts use. That data never leaves Snowflake, and your existing row access and masking policies still apply.\u003C/p\u003E\n","\u003Cp\u003EUnder the hood, a dashboard is a single \u003Ccode\u003E.dash\u003C/code\u003E file in Snowsight Workspaces. Each tile runs live SQL against tables or a semantic view in your account. Filters, chart actions, and hierarchy drilldowns take you from a headline number to the rows behind it without leaving the page.\u003C/p\u003E\n","\u003Cp\u003EThe dashboard we're building is called \u003Cstrong\u003ERevenue Pulse\u003C/strong\u003E. It runs on synthetic data for a fictional B2B software company: 54 accounts, 3 product lines, and 24 months of revenue through September 30, 2026. The data has a story built in. Q3 2026 revenue is $1.09M behind target, and most of the gap sits in EMEA Enterprise.\u003C/p\u003E\n","\u003Ch3\u003EWhat You'll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to load a small demo dataset and semantic view with one SQL file\u003C/li\u003E\u003Cli\u003EHow to open a \u003Ccode\u003E.dash\u003C/code\u003E file in Snowsight Workspaces\u003C/li\u003E\u003Cli\u003EHow filters, brushing, click-to-filter, and hierarchy drilldown work in a dashboard\u003C/li\u003E\u003Cli\u003EHow to publish a dashboard to Snowflake CoWork and ask follow-up questions about it\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Build\u003C/h3\u003E\n","\u003Cp\u003EYou'll set up the data and deploy a ready-made dashboard in your own account, so you get value from it right away:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\u003Cstrong\u003ESetup:\u003C/strong\u003E download three files, point them at a schema you already have, and run one SQL file that loads a small synthetic dataset and a semantic view in about 10 seconds.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EDeploy the dashboard:\u003C/strong\u003E upload the dashboard file to Workspaces and open it.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EInvestigate the shortfall:\u003C/strong\u003E brush a date range on the trend, click a region to filter every chart, and drill from region to segment to account.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAsk why in CoWork:\u003C/strong\u003E publish the dashboard to Snowflake CoWork and ask why the numbers moved.\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EClean up:\u003C/strong\u003E run a cleanup script that removes everything.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe diagram shows how the pieces fit together. \u003Ccode\u003Esetup.sql\u003C/code\u003E creates three tables and a semantic view on top of them. The dashboard queries the semantic view, and publishing it creates a CoWork artifact that a viewer role can open. \u003Ccode\u003Ecleanup.sql\u003C/code\u003E removes the tables and semantic view.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/architecture.png?v=a10de302\" alt=\"Architecture of the tutorial: setup.sql creates the CUSTOMERS, PRODUCTS, and REVENUE_MONTHLY tables, which feed REVENUE_SEMANTIC_VIEW. revenue_pulse.dash selects from the semantic view, is published as the Revenue Pulse CoWork artifact, and is shared with a viewer role that has Can view access and SELECT. Follow-up questions in CoWork query the semantic view with the viewer's privileges. cleanup.sql drops the semantic view and tables\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe result is a four-tab Revenue Pulse dashboard running on live queries. The tabs are \u003Cstrong\u003EOverview\u003C/strong\u003E, \u003Cstrong\u003EHierarchical Chart\u003C/strong\u003E, \u003Cstrong\u003EHierarchical Table\u003C/strong\u003E, and \u003Cstrong\u003EData Source\u003C/strong\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/dashboard-complete.png?v=a10de302\" alt=\"Overview tab of the Revenue Pulse dashboard with KPI sparklines, a monthly trend, regional bars, a heatmap, and driver and account charts\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EWhat You'll Need\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EAccess to a \u003Ca href=\"https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&utm_cta=developer-guides\"\u003ESnowflake account\u003C/a\u003E\u003C/li\u003E\u003Cli\u003EAn existing schema you can create objects in, and a warehouse you can use. Your role needs \u003Ccode\u003EUSAGE\u003C/code\u003E on the database and schema, plus \u003Ccode\u003ECREATE TABLE\u003C/code\u003E and \u003Ccode\u003ECREATE SEMANTIC VIEW\u003C/code\u003E on the schema. If your role owns the schema, it already has these. The same role runs the cleanup\u003C/li\u003E\u003Cli\u003EAccess to \u003Ca href=\"https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards\"\u003ESnowflake Dashboards\u003C/a\u003E (public preview) in Snowsight Workspaces\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EEverything runs in Snowsight. You don't need Python, a CLI, or a Git integration.\u003C/p\u003E\n","\u003Ch2\u003ESetup\u003C/h2\u003E\n","\u003Cp\u003EThe three files you need are in the \u003Ccode\u003Egetting-started/\u003C/code\u003E folder of the \u003Ca href=\"https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/tree/main/getting-started\"\u003Ecompanion repository\u003C/a\u003E:\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EFile\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EWhat it does\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/blob/main/getting-started/setup.sql\"\u003E\u003Ccode\u003Esetup.sql\u003C/code\u003E\u003C/a\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ECreates three tables of synthetic data and the \u003Ccode\u003EREVENUE_SEMANTIC_VIEW\u003C/code\u003E semantic view in your schema\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/blob/main/getting-started/revenue_pulse.dash\"\u003E\u003Ccode\u003Erevenue_pulse.dash\u003C/code\u003E\u003C/a\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EThe finished dashboard: tiles, filters, layout, and SQL in one file\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/blob/main/getting-started/cleanup.sql\"\u003E\u003Ccode\u003Ecleanup.sql\u003C/code\u003E\u003C/a\u003E\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EDrops the four objects \u003Ccode\u003Esetup.sql\u003C/code\u003E created, for when you're done\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Cp\u003EOn each file's GitHub page, select \u003Cstrong\u003EDownload raw file\u003C/strong\u003E.\u003C/p\u003E\n","\u003Ch3\u003EPoint the Files at Your Schema\u003C/h3\u003E\n","\u003Cp\u003E\u003Ccode\u003ETEMP\u003C/code\u003E and \u003Ccode\u003ECNANTASENAMAT\u003C/code\u003E are the author's own database and schema, used here as placeholders. Replace them with a database and schema of your choice that you can create objects in. Do this before uploading the files.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn \u003Ccode\u003Esetup.sql\u003C/code\u003E and \u003Ccode\u003Ecleanup.sql\u003C/code\u003E, replace \u003Ccode\u003ETEMP\u003C/code\u003E and \u003Ccode\u003ECNANTASENAMAT\u003C/code\u003E in the two \u003Ccode\u003EUSE\u003C/code\u003E lines near the top. Each line has a comment marking what to replace:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE DATABASE TEMP;   -- Replace TEMP with your own database\nUSE SCHEMA CNANTASENAMAT;   -- Replace CNANTASENAMAT with your own schema in that database\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFor example, \u003Ccode\u003EUSE DATABASE ANALYTICS;\u003C/code\u003E and \u003Ccode\u003EUSE SCHEMA MY_SANDBOX;\u003C/code\u003E. Everything after these lines uses names relative to that schema.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIn \u003Ccode\u003Erevenue_pulse.dash\u003C/code\u003E, replace every \u003Ccode\u003ETEMP.CNANTASENAMAT\u003C/code\u003E with your own \u003Ccode\u003EDATABASE.SCHEMA\u003C/code\u003E, for example \u003Ccode\u003EANALYTICS.MY_SANDBOX\u003C/code\u003E. The dashboard's queries use fully qualified names, so they work for anyone you share it with.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EPick a schema that doesn't already contain tables named \u003Ccode\u003ECUSTOMERS\u003C/code\u003E, \u003Ccode\u003EPRODUCTS\u003C/code\u003E, or \u003Ccode\u003EREVENUE_MONTHLY\u003C/code\u003E, or a semantic view named \u003Ccode\u003EREVENUE_SEMANTIC_VIEW\u003C/code\u003E. The setup replaces objects with those names.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ELoad the Data\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EIn Snowsight, go to \u003Cstrong\u003EProjects » Workspaces\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EIn \u003Cstrong\u003EMy Workspace\u003C/strong\u003E, select \u003Cstrong\u003E+ Add New » Upload Files\u003C/strong\u003E and upload \u003Ccode\u003Esetup.sql\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EOpen \u003Ccode\u003Esetup.sql\u003C/code\u003E. In the editor, pick your role and a warehouse.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ERun All\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe script finishes in about 10 seconds. Its last statement returns one row:\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ECUSTOMERS\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EPRODUCTS\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003EREVENUE_ROWS\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E54\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E3\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E3888\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","\u003Cp\u003EIf you see those numbers, the data is ready. The script is safe to run again: it replaces the tables and semantic view each time, and keeps any grants you've added to them.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote:\u003C/strong\u003E The revenue rows are packed into one \u003Ccode\u003EINSERT\u003C/code\u003E to keep the file small. You don't need to read it. The table definitions at the top and the semantic view at the bottom are the parts worth a look.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch2\u003EExplore the Dashboard\u003C/h2\u003E\n","\u003Ch3\u003EOpen the Dashboard\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003ESelect \u003Cstrong\u003E+ Add New » Upload Files\u003C/strong\u003E again and upload \u003Ccode\u003Erevenue_pulse.dash\u003C/code\u003E.\u003C/li\u003E\u003Cli\u003EOpen \u003Ccode\u003Erevenue_pulse.dash\u003C/code\u003E. Snowsight renders it as a dashboard rather than as text.\u003C/li\u003E\u003Cli\u003ESelect \u003Cstrong\u003ERun all\u003C/strong\u003E if the tiles don't load on their own.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe KPI row shows the Q3 2026 headline: net revenue of \u003Cstrong\u003E$6.9M\u003C/strong\u003E, up 0.8% year over year, \u003Cstrong\u003E86.3%\u003C/strong\u003E target attainment, a variance of about \u003Cstrong\u003E−$1.09M\u003C/strong\u003E (the card rounds it to −$1M), and 71% gross margin.\u003C/p\u003E\n","\u003Ch3\u003EChart Actions\u003C/h3\u003E\n","\u003Cp\u003E\u003Ca href=\"https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards#chart-actions\"\u003EChart actions\u003C/a\u003E are interactions an author adds to a chart. When a viewer clicks or drags on that chart (the source tile), other tiles (the targets) respond. A filter action re-runs their queries for just the selection. A highlight action keeps all the data and dims what doesn't match. Revenue Pulse already has filter actions wired up, so you can use them right away.\u003C/p\u003E\n","\u003Cp\u003EThe dashboard isn't a static report: every chart doubles as a filter. The animation below scrolls from the KPI cards through the trend, regional, heatmap, driver, and account charts. It then clicks a region on the variance-by-region chart, and the rest of the dashboard narrows to that region. That click is one of several chart actions. In the next sections you'll brush a date range on the trend, click a region or heatmap cell to filter every chart, and drill down from region to segment to account.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/dashboard-chart-actions.gif?v=a10de302\" alt=\"Animated demo of the Revenue Pulse dashboard: scrolling the KPI tiles and charts, then clicking a region on the variance bars to filter the other charts\"\u003E\u003C/p\u003E\n","\u003Cp\u003ETry each of these on the \u003Cstrong\u003EOverview\u003C/strong\u003E tab, and clear the selection before the next one.\u003C/p\u003E\n","\u003Ch3\u003EBrush the Trend\u003C/h3\u003E\n","\u003Cp\u003EDrag across a range of months on \u003Cstrong\u003EMonthly Net Revenue vs Target\u003C/strong\u003E. The chart zooms to those months, and the KPI cards, regional bars, and heatmap recalculate for the range. Clear the \u003Cstrong\u003EFiltering\u003C/strong\u003E chip on the tile to undo it.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/trend-brush-active.png?v=a10de302\" alt=\"Trend brushed across several months: the tile shows a Filtering chip and the other charts recalculate\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EClick a Region\u003C/h3\u003E\n","\u003Cp\u003EClick the \u003Cstrong\u003EEMEA\u003C/strong\u003E bar on \u003Cstrong\u003EVariance to Target by Region\u003C/strong\u003E. The other tiles filter to EMEA, where attainment drops to about 70%. Clear \u003Cstrong\u003EDrill: region path\u003C/strong\u003E at the top to reset.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/regional-bar-filter-emea.png?v=a10de302\" alt=\"Regional variance bars after clicking EMEA, with the other tiles filtered to that region\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EClick a Heatmap Cell\u003C/h3\u003E\n","\u003Cp\u003EOn \u003Cstrong\u003ETarget Attainment\u003C/strong\u003E, the darkest cell is EMEA Enterprise at \u003Cstrong\u003E57.9%\u003C/strong\u003E. Click it to filter the rest of the dashboard to that region and segment. A \u003Cstrong\u003EFiltering EMEA, Enterprise\u003C/strong\u003E chip appears above the heatmap, and every other chart updates to that slice. The scorecards drop to about $1.1M net revenue, 57.9% attainment, and a variance of about −$779K, and the variance bars switch from regions to the six EMEA Enterprise accounts. Select the \u003Cstrong\u003E×\u003C/strong\u003E on the chip to clear it.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/heatmap-cell-filter.png?v=a10de302\" alt=\"After clicking the EMEA Enterprise cell on the Target Attainment heatmap: a Filtering EMEA, Enterprise chip sits above the heatmap, and the variance bars beside it list the six EMEA Enterprise accounts\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EDrill the Hierarchy\u003C/h3\u003E\n","\u003Cp\u003EOpen the \u003Cstrong\u003EHierarchical Chart\u003C/strong\u003E tab. Click \u003Cstrong\u003EEMEA\u003C/strong\u003E, then \u003Cstrong\u003EEnterprise\u003C/strong\u003E, to reach its six accounts. The largest miss is Demo EMEA Enterprise 05, at about −$349K. Use the level trail to return to the top.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/hierarchy-drill-region.png?v=a10de302\" alt=\"Hierarchical Chart tab at the region level, with EMEA furthest below target and the account table sorted by variance\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe \u003Cstrong\u003EHierarchical Table\u003C/strong\u003E tab shows the same region › segment › account path as an expandable grid.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/hierarchy-table.png?v=a10de302\" alt=\"Hierarchical Table tab at the region level, with EMEA at 70.1% attainment, APAC at 83%, and Americas at 106.1%\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EUse the Header Filters\u003C/h3\u003E\n","\u003Cp\u003ESet \u003Cstrong\u003ERegion = EMEA\u003C/strong\u003E and \u003Cstrong\u003ESegment = Enterprise\u003C/strong\u003E from the filter bar. These filters apply across every tab, which makes them the quickest way to compare one slice against another.\u003C/p\u003E\n","\u003Ch2\u003EAsk Why in CoWork\u003C/h2\u003E\n","\u003Cp\u003EThe dashboard has shown you where the gap is: EMEA Enterprise, and three of its accounts in particular. The next question is why. Publish the dashboard to \u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork\"\u003ESnowflake CoWork\u003C/a\u003E and you can ask that question in plain language, right next to the charts. Anyone you share it with can do the same.\u003C/p\u003E\n","\u003Ch3\u003EPublish the Dashboard\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003EWith \u003Ccode\u003Erevenue_pulse.dash\u003C/code\u003E open, select \u003Cstrong\u003EShare\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EAdd a role with \u003Cstrong\u003ECan view\u003C/strong\u003E access, then publish. Your own role works; add a teammate's role too if you want them to see it.\u003C/li\u003E\u003Cli\u003EOpen \u003Cstrong\u003EArtifacts\u003C/strong\u003E in CoWork and select \u003Cstrong\u003ERevenue Pulse\u003C/strong\u003E.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EViewers run the dashboard with their own privileges, so their role needs \u003Ccode\u003ESELECT\u003C/code\u003E on the three tables and the semantic view, plus a warehouse. Publishing needs the \u003Ccode\u003EMANAGE ACCESS ON DASHBOARD ARTIFACTS\u003C/code\u003E privilege, which is \u003Ca href=\"https://docs.snowflake.com/en/release-notes/bcr-bundles/un-bundled/bcr-manage-access-dashboard-artifacts\"\u003Egranted to \u003Ccode\u003EPUBLIC\u003C/code\u003E by default\u003C/a\u003E.\u003C/p\u003E\n","\u003Ch3\u003EAsk a Follow-Up Question\u003C/h3\u003E\n","\u003Cp\u003EIn the box below the dashboard, ask:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EWhy is EMEA Enterprise behind target in Q3 2026? Quantify the drivers.\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ECoWork runs queries against the same data and answers in a side panel, with a table of the drivers behind the miss. In the run below, it found EMEA Enterprise finished Q3 2026 about $779K below target, at 57.9% attainment. Renewal delays explained about 44% of the shortfall, a contract downsize about 33%, and discounts and service credits about 23%. Your answer may be worded differently, but the numbers come from the same data.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/cowork-ask-why.gif?v=a10de302\" alt=\"Animated demo in CoWork: typing why EMEA Enterprise is behind target in Q3 2026, then the answer appearing in a side panel with a table of the drivers behind the shortfall\"\u003E\u003C/p\u003E\n","\u003Cp\u003ETry a follow-up of your own, such as which accounts to call first, or how EMEA Enterprise compares with the same quarter last year.\u003C/p\u003E\n","\u003Ch2\u003EClean Up\u003C/h2\u003E\n","\u003Cp\u003EWhen you're done:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ERemove the dashboard's roles in \u003Cstrong\u003EShare\u003C/strong\u003E and delete the Revenue Pulse artifact in CoWork.\u003C/li\u003E\u003Cli\u003EUpload \u003Ccode\u003Ecleanup.sql\u003C/code\u003E, open it, and select \u003Cstrong\u003ERun All\u003C/strong\u003E with the same role you used for \u003Ccode\u003Esetup.sql\u003C/code\u003E. It drops the four objects the setup created and leaves your schema in place:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE DATABASE TEMP;   -- Replace TEMP with your own database\nUSE SCHEMA CNANTASENAMAT;   -- Replace CNANTASENAMAT with your own schema in that database\n\nDROP SEMANTIC VIEW IF EXISTS REVENUE_SEMANTIC_VIEW;\nDROP TABLE IF EXISTS REVENUE_MONTHLY;\nDROP TABLE IF EXISTS PRODUCTS;\nDROP TABLE IF EXISTS CUSTOMERS;\n\u003C/code\u003E\u003C/pre\u003E\n\u003Col start=\"3\"\u003E\u003Cli\u003EDelete \u003Ccode\u003Esetup.sql\u003C/code\u003E, \u003Ccode\u003Erevenue_pulse.dash\u003C/code\u003E, and \u003Ccode\u003Ecleanup.sql\u003C/code\u003E from your workspace.\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Cp\u003EYou loaded a dataset, deployed a dashboard file, traced a $1.09M revenue gap to EMEA Enterprise, and asked CoWork why it happened. The \u003Ccode\u003E.dash\u003C/code\u003E file you opened holds every tile, filter, chart action, and SQL query, so it's easy to version, share, and reuse.\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EOne SQL file can set up the tables and semantic view a dashboard needs\u003C/li\u003E\u003Cli\u003EA \u003Ccode\u003E.dash\u003C/code\u003E file opens in Workspaces as a working dashboard\u003C/li\u003E\u003Cli\u003EBrushing, click-to-filter, and hierarchy drilldown let you move from a headline number to the accounts behind it\u003C/li\u003E\u003Cli\u003EPublished dashboards run with each viewer's own privileges\u003C/li\u003E\u003Cli\u003EIn CoWork, you can ask follow-up questions about a dashboard and get answers from the same data\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/LIMITEDACCESS/cowork-dashboards\"\u003EDashboards in Snowflake CoWork\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces\"\u003EWorkspaces\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/views-semantic/overview\"\u003ESnowflake semantic views\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork/artifacts\"\u003EArtifacts in Snowflake CoWork\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Getting Started with Snowflake Dashboards","isDeveloperGuidesPage":false,":type":"snowflake-site/components/contentfragment",":items":{},":itemsOrder":[],"elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"## Overview\n\nA revenue number that misses target raises questions right away. Which region is behind? Which segment? Which accounts? On many teams the answers live in exported spreadsheets or static report decks. They go stale as soon as the data changes, and every follow-up question means another export or another request to an analyst.\n\n[Snowflake Dashboards](https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards) (public preview) give the team one shared source of truth that they can also talk to. Analysts build a dashboard by describing it to Cortex Code (CoCo), then share it with the right roles. Anyone with access can open it in Snowflake CoWork and ask it questions: summarize what it shows, explain what drove a change, or narrow it to one segment. The answers come from the same governed data the charts use. That data never leaves Snowflake, and your existing row access and masking policies still apply.\n\nUnder the hood, a dashboard is a single `.dash` file in Snowsight Workspaces. Each tile runs live SQL against tables or a semantic view in your account. Filters, chart actions, and hierarchy drilldowns take you from a headline number to the rows behind it without leaving the page.\n\nThe dashboard we're building is called **Revenue Pulse**. It runs on synthetic data for a fictional B2B software company: 54 accounts, 3 product lines, and 24 months of revenue through September 30, 2026. The data has a story built in. Q3 2026 revenue is $1.09M behind target, and most of the gap sits in EMEA Enterprise.\n### What You'll Learn\n- How to load a small demo dataset and semantic view with one SQL file\n- How to open a `.dash` file in Snowsight Workspaces\n- How filters, brushing, click-to-filter, and hierarchy drilldown work in a dashboard\n- How to publish a dashboard to Snowflake CoWork and ask follow-up questions about it\n\n### What You'll Build\nYou'll set up the data and deploy a ready-made dashboard in your own account, so you get value from it right away:\n\n1. **Setup:** download three files, point them at a schema you already have, and run one SQL file that loads a small synthetic dataset and a semantic view in about 10 seconds.\n2. **Deploy the dashboard:** upload the dashboard file to Workspaces and open it.\n3. **Investigate the shortfall:** brush a date range on the trend, click a region to filter every chart, and drill from region to segment to account.\n4. **Ask why in CoWork:** publish the dashboard to Snowflake CoWork and ask why the numbers moved.\n5. **Clean up:** run a cleanup script that removes everything.\n\nThe diagram shows how the pieces fit together. `setup.sql` creates three tables and a semantic view on top of them. The dashboard queries the semantic view, and publishing it creates a CoWork artifact that a viewer role can open. `cleanup.sql` removes the tables and semantic view.\n\n![Architecture of the tutorial: setup.sql creates the CUSTOMERS, PRODUCTS, and REVENUE_MONTHLY tables, which feed REVENUE_SEMANTIC_VIEW. revenue_pulse.dash selects from the semantic view, is published as the Revenue Pulse CoWork artifact, and is shared with a viewer role that has Can view access and SELECT. Follow-up questions in CoWork query the semantic view with the viewer's privileges. cleanup.sql drops the semantic view and tables](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/architecture.png?v=a10de302)\n\nThe result is a four-tab Revenue Pulse dashboard running on live queries. The tabs are **Overview**, **Hierarchical Chart**, **Hierarchical Table**, and **Data Source**.\n\n![Overview tab of the Revenue Pulse dashboard with KPI sparklines, a monthly trend, regional bars, a heatmap, and driver and account charts](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/dashboard-complete.png?v=a10de302)\n\n### What You'll Need\n- Access to a [Snowflake account](https://signup.snowflake.com/?utm_source=snowflake-devrel&utm_medium=developer-guides&utm_cta=developer-guides)\n- An existing schema you can create objects in, and a warehouse you can use. Your role needs `USAGE` on the database and schema, plus `CREATE TABLE` and `CREATE SEMANTIC VIEW` on the schema. If your role owns the schema, it already has these. The same role runs the cleanup\n- Access to [Snowflake Dashboards](https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards) (public preview) in Snowsight Workspaces\n\nEverything runs in Snowsight. You don't need Python, a CLI, or a Git integration.\n\n## Setup\n\nThe three files you need are in the `getting-started/` folder of the [companion repository](https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/tree/main/getting-started):\n\n| File | What it does |\n|---|---|\n| [`setup.sql`](https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/blob/main/getting-started/setup.sql) | Creates three tables of synthetic data and the `REVENUE_SEMANTIC_VIEW` semantic view in your schema |\n| [`revenue_pulse.dash`](https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/blob/main/getting-started/revenue_pulse.dash) | The finished dashboard: tiles, filters, layout, and SQL in one file |\n| [`cleanup.sql`](https://github.com/Snowflake-Labs/getting-started-with-snowflake-dashboards/blob/main/getting-started/cleanup.sql) | Drops the four objects `setup.sql` created, for when you're done |\n\nOn each file's GitHub page, select **Download raw file**.\n\n### Point the Files at Your Schema\n\n`TEMP` and `CNANTASENAMAT` are the author's own database and schema, used here as placeholders. Replace them with a database and schema of your choice that you can create objects in. Do this before uploading the files.\n\n1. In `setup.sql` and `cleanup.sql`, replace `TEMP` and `CNANTASENAMAT` in the two `USE` lines near the top. Each line has a comment marking what to replace:\n\n   ```sql\n   USE DATABASE TEMP;   -- Replace TEMP with your own database\n   USE SCHEMA CNANTASENAMAT;   -- Replace CNANTASENAMAT with your own schema in that database\n   ```\n\n   For example, `USE DATABASE ANALYTICS;` and `USE SCHEMA MY_SANDBOX;`. Everything after these lines uses names relative to that schema.\n2. In `revenue_pulse.dash`, replace every `TEMP.CNANTASENAMAT` with your own `DATABASE.SCHEMA`, for example `ANALYTICS.MY_SANDBOX`. The dashboard's queries use fully qualified names, so they work for anyone you share it with.\n\n\u003E Pick a schema that doesn't already contain tables named `CUSTOMERS`, `PRODUCTS`, or `REVENUE_MONTHLY`, or a semantic view named `REVENUE_SEMANTIC_VIEW`. The setup replaces objects with those names.\n\n### Load the Data\n\n1. In Snowsight, go to **Projects » Workspaces**.\n2. In **My Workspace**, select **+ Add New » Upload Files** and upload `setup.sql`.\n3. Open `setup.sql`. In the editor, pick your role and a warehouse.\n4. Select **Run All**.\n\nThe script finishes in about 10 seconds. Its last statement returns one row:\n\n| CUSTOMERS | PRODUCTS | REVENUE_ROWS |\n|---|---|---|\n| 54 | 3 | 3888 |\n\nIf you see those numbers, the data is ready. The script is safe to run again: it replaces the tables and semantic view each time, and keeps any grants you've added to them.\n\n\u003E **Note:** The revenue rows are packed into one `INSERT` to keep the file small. You don't need to read it. The table definitions at the top and the semantic view at the bottom are the parts worth a look.\n\n## Explore the Dashboard\n\n### Open the Dashboard\n\n1. Select **+ Add New » Upload Files** again and upload `revenue_pulse.dash`.\n2. Open `revenue_pulse.dash`. Snowsight renders it as a dashboard rather than as text.\n3. Select **Run all** if the tiles don't load on their own.\n\nThe KPI row shows the Q3 2026 headline: net revenue of **$6.9M**, up 0.8% year over year, **86.3%** target attainment, a variance of about **−$1.09M** (the card rounds it to −$1M), and 71% gross margin.\n\n### Chart Actions\n\n[Chart actions](https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards#chart-actions) are interactions an author adds to a chart. When a viewer clicks or drags on that chart (the source tile), other tiles (the targets) respond. A filter action re-runs their queries for just the selection. A highlight action keeps all the data and dims what doesn't match. Revenue Pulse already has filter actions wired up, so you can use them right away.\n\nThe dashboard isn't a static report: every chart doubles as a filter. The animation below scrolls from the KPI cards through the trend, regional, heatmap, driver, and account charts. It then clicks a region on the variance-by-region chart, and the rest of the dashboard narrows to that region. That click is one of several chart actions. In the next sections you'll brush a date range on the trend, click a region or heatmap cell to filter every chart, and drill down from region to segment to account.\n\n![Animated demo of the Revenue Pulse dashboard: scrolling the KPI tiles and charts, then clicking a region on the variance bars to filter the other charts](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/dashboard-chart-actions.gif?v=a10de302)\n\nTry each of these on the **Overview** tab, and clear the selection before the next one.\n\n### Brush the Trend\nDrag across a range of months on **Monthly Net Revenue vs Target**. The chart zooms to those months, and the KPI cards, regional bars, and heatmap recalculate for the range. Clear the **Filtering** chip on the tile to undo it.\n\n![Trend brushed across several months: the tile shows a Filtering chip and the other charts recalculate](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/trend-brush-active.png?v=a10de302)\n\n### Click a Region\nClick the **EMEA** bar on **Variance to Target by Region**. The other tiles filter to EMEA, where attainment drops to about 70%. Clear **Drill: region path** at the top to reset.\n\n![Regional variance bars after clicking EMEA, with the other tiles filtered to that region](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/regional-bar-filter-emea.png?v=a10de302)\n\n### Click a Heatmap Cell\nOn **Target Attainment**, the darkest cell is EMEA Enterprise at **57.9%**. Click it to filter the rest of the dashboard to that region and segment. A **Filtering EMEA, Enterprise** chip appears above the heatmap, and every other chart updates to that slice. The scorecards drop to about $1.1M net revenue, 57.9% attainment, and a variance of about −$779K, and the variance bars switch from regions to the six EMEA Enterprise accounts. Select the **×** on the chip to clear it.\n\n![After clicking the EMEA Enterprise cell on the Target Attainment heatmap: a Filtering EMEA, Enterprise chip sits above the heatmap, and the variance bars beside it list the six EMEA Enterprise accounts](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/heatmap-cell-filter.png?v=a10de302)\n\n### Drill the Hierarchy\nOpen the **Hierarchical Chart** tab. Click **EMEA**, then **Enterprise**, to reach its six accounts. The largest miss is Demo EMEA Enterprise 05, at about −$349K. Use the level trail to return to the top.\n\n![Hierarchical Chart tab at the region level, with EMEA furthest below target and the account table sorted by variance](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/hierarchy-drill-region.png?v=a10de302)\n\nThe **Hierarchical Table** tab shows the same region › segment › account path as an expandable grid.\n\n![Hierarchical Table tab at the region level, with EMEA at 70.1% attainment, APAC at 83%, and Americas at 106.1%](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/hierarchy-table.png?v=a10de302)\n\n### Use the Header Filters\nSet **Region = EMEA** and **Segment = Enterprise** from the filter bar. These filters apply across every tab, which makes them the quickest way to compare one slice against another.\n\n## Ask Why in CoWork\n\nThe dashboard has shown you where the gap is: EMEA Enterprise, and three of its accounts in particular. The next question is why. Publish the dashboard to [Snowflake CoWork](https://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork) and you can ask that question in plain language, right next to the charts. Anyone you share it with can do the same.\n\n### Publish the Dashboard\n\n1. With `revenue_pulse.dash` open, select **Share**.\n2. Add a role with **Can view** access, then publish. Your own role works; add a teammate's role too if you want them to see it.\n3. Open **Artifacts** in CoWork and select **Revenue Pulse**.\n\nViewers run the dashboard with their own privileges, so their role needs `SELECT` on the three tables and the semantic view, plus a warehouse. Publishing needs the `MANAGE ACCESS ON DASHBOARD ARTIFACTS` privilege, which is [granted to `PUBLIC` by default](https://docs.snowflake.com/en/release-notes/bcr-bundles/un-bundled/bcr-manage-access-dashboard-artifacts).\n\n### Ask a Follow-Up Question\n\nIn the box below the dashboard, ask:\n\n```\nWhy is EMEA Enterprise behind target in Q3 2026? Quantify the drivers.\n```\n\nCoWork runs queries against the same data and answers in a side panel, with a table of the drivers behind the miss. In the run below, it found EMEA Enterprise finished Q3 2026 about $779K below target, at 57.9% attainment. Renewal delays explained about 44% of the shortfall, a contract downsize about 33%, and discounts and service credits about 23%. Your answer may be worded differently, but the numbers come from the same data.\n\n![Animated demo in CoWork: typing why EMEA Enterprise is behind target in Q3 2026, then the answer appearing in a side panel with a table of the drivers behind the shortfall](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/getting-started-with-snowflake-dashboards/cowork-ask-why.gif?v=a10de302)\n\nTry a follow-up of your own, such as which accounts to call first, or how EMEA Enterprise compares with the same quarter last year.\n\n## Clean Up\n\nWhen you're done:\n\n1. Remove the dashboard's roles in **Share** and delete the Revenue Pulse artifact in CoWork.\n2. Upload `cleanup.sql`, open it, and select **Run All** with the same role you used for `setup.sql`. It drops the four objects the setup created and leaves your schema in place:\n\n```sql\nUSE DATABASE TEMP;   -- Replace TEMP with your own database\nUSE SCHEMA CNANTASENAMAT;   -- Replace CNANTASENAMAT with your own schema in that database\n\nDROP SEMANTIC VIEW IF EXISTS REVENUE_SEMANTIC_VIEW;\nDROP TABLE IF EXISTS REVENUE_MONTHLY;\nDROP TABLE IF EXISTS PRODUCTS;\nDROP TABLE IF EXISTS CUSTOMERS;\n```\n\n3. Delete `setup.sql`, `revenue_pulse.dash`, and `cleanup.sql` from your workspace.\n\n## Conclusion And Resources\n\nYou loaded a dataset, deployed a dashboard file, traced a $1.09M revenue gap to EMEA Enterprise, and asked CoWork why it happened. The `.dash` file you opened holds every tile, filter, chart action, and SQL query, so it's easy to version, share, and reuse.\n\n### What You Learned\n- One SQL file can set up the tables and semantic view a dashboard needs\n- A `.dash` file opens in Workspaces as a working dashboard\n- Brushing, click-to-filter, and hierarchy drilldown let you move from a headline number to the accounts behind it\n- Published dashboards run with each viewer's own privileges\n- In CoWork, you can ask follow-up questions about a dashboard and get answers from the same data\n\n### Related Resources\n- [Dashboards in Snowflake CoWork](https://docs.snowflake.com/en/LIMITEDACCESS/cowork-dashboards)\n- [Workspaces](https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces)\n- [Snowflake semantic views](https://docs.snowflake.com/en/user-guide/views-semantic/overview)\n- [Artifacts in Snowflake CoWork](https://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork/artifacts)\n\n",":type":"text/x-markdown","multiValue":false},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image",":type":"text/plain","multiValue":false}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-bf8a7b4230","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-81cf0a359b",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-c41efcc3d6","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2026-11-05",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-4c68832977","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. 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