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pre[class*=language-]{background-color:rgba(var(--ui-12-rgb),.5);color:var(--text-01);text-shadow:none;padding:var(--spacing-00);border-radius:var(--spacing-00);font-size:smaller}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"responsivegrid":{"columnClassNames":{"quickstart_hero":"aem-GridColumn aem-GridColumn--default--12","flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,":items":{"quickstart_hero":{"id":"quickstart-hero-50eaf0ebb0","isDeveloperGuidesPage":false,":type":"snowflake-site/components/quickstart/quickstart-hero","fragmentPath":"/content/dam/snowflake-site/en/content-fragments/quickstarts/streamline-healthcare-cdc-ddb-and-openflow","quickstartHeroBreadcrumbs":[{"title":"Streamlining Healthcare Claims Change Data Capture Processing Using Amazon DynamoDB and Snowflake OpenFlow","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides/streamline-healthcare-cdc-ddb-and-openflow","currentPage":true},{"title":"Guides","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides","currentPage":false},{"title":"Snowflake for 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Snowflake OpenFlow"],"type":"heading2",":type":"snowflake-site/components/title-v2"},"quickstartHeroAuthor":"James Sun, Snowflake"},"flexible_column_cont":{"id":"flexible-column-container-caa68dcb62","propertiesId":"quickstart-template-main-flexible-container","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-31ffec657c",":items":{"contentfragment":{"id":"contentfragment-02d829a21c","description":"","paragraphs":["<!---------------------------->\n","\u003Ch2\u003EOverview\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EIn a healthcare claims processing system, \u003Ca href=\"https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Introduction.html\"\u003EAmazon DynamoDB\u003C/a\u003E can serve as an effective front-end database due to its high scalability, low-latency performance, and schema flexibility. It allows real-time ingestion and access to diverse, evolving claim event data such as status changes, user interactions, or system-generated events without the constraints of a rigid relational schema. This is especially valuable in front-end applications where speed and adaptability are critical. On the back end, Snowflake complements DynamoDB by handling complex analytics, aggregations, data sharing and reporting. Claim data can be streamed in near real-time from DynamoDB into Snowflake via \u003Ca href=\"/en/product/features/openflow/\"\u003EOpenflow\u003C/a\u003E seamlessly, where advanced SQL queries, joins, and business intelligence tools can be applied to support audits, compliance checks, long-term trends and securely shared with teams across the globe. Together, this architecture balances speed and flexibility at the front with powerful analytics and data integrity at the back.\u003C/p\u003E\n","\u003Cp\u003EThis guickstart will walk you through how to build CDC pipelines to synchronize the front-end DynamoDB and back-end Snowflake tables for processing real-time insurance claims\u003C/p\u003E\n","\u003Cp\u003EBelow is a schematic diagram of the demo. The CDC events in DynamoDB are captured in a \u003Ca href=\"https://docs.aws.amazon.com/streams/latest/dev/key-concepts.html\"\u003EKinesis data stream\u003C/a\u003E, we then use an Openflow connector to consume those events and they are streamed into a CDC table which holds the events yet to be merged with the destination table, while all historical events are loaded into the event history table for logging and tracking purposes. After the CDC events are merged, the source DynamoDB table and the destination Snowflake table are synchronized.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/demo-diagram.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EWhat You Will Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to set up Change Data Capture (CDC) between Amazon DynamoDB and Snowflake\u003C/li\u003E\u003Cli\u003EHow to configure and use Snowflake Openflow for real-time data synchronization\u003C/li\u003E\u003Cli\u003EHow to capture and process DynamoDB stream events using Kinesis Data Streams\u003C/li\u003E\u003Cli\u003EHow to transform semi-structured JSON data for analytics in Openflow\u003C/li\u003E\u003Cli\u003EHow to implement and monitor real-time CDC operations (INSERT, MODIFY, REMOVE)\u003C/li\u003E\u003Cli\u003EBest practices for healthcare claims data processing in a hybrid architecture\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You will Build\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA complete CDC pipeline that synchronizes healthcare insurance claims data between DynamoDB and Snowflake\u003C/li\u003E\u003Cli\u003EAn Openflow connector that consumes, transforms, and loads CDC events into Snowflake\u003C/li\u003E\u003Cli\u003EA set of Snowflake tables for storing and tracking claim events, including:\n\u003Cul\u003E\u003Cli\u003EA destination table synchronized with the source DynamoDB table\u003C/li\u003E\u003Cli\u003EA CDC operations table for staging changes\u003C/li\u003E\u003Cli\u003EAn event history table for auditing and tracking all data modifications\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003ESQL merge operations that maintain data consistency across both systems\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPrerequisites OR What You Will Need\u003C/h3\u003E\n","\u003Cp\u003EBefore proceeding with the quickstart, ensure you have:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESnowflake and AWS Account Access\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EA Snowflake account in one of the AWS commercial \u003Ca href=\"https://docs.snowflake.com/en/user-guide/intro-regions#label-na-general-regions\"\u003Eregions\u003C/a\u003E. If you do not have one you can register for a \u003Ca href=\"https://signup.snowflake.com/?utm_cta=quickstart-insurance-claims-dynamodb-openflow-cdc\"\u003Efree trial account\u003C/a\u003E.\u003C/li\u003E\u003Cli\u003EAn AWS account with permissions to create the required resources using \u003Ca href=\"https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html\"\u003ECloudformation\u003C/a\u003E.\u003C/li\u003E\u003Cli\u003EAccess to the AWS Management Console and \u003Ca href=\"https://docs.aws.amazon.com/cli/v1/userguide/cli-chap-configure.html\"\u003EAWS CLI\u003C/a\u003E configured with required credentials.\u003C/li\u003E\u003Cli\u003EA Snowflake account with permissions to run queries and create \u003Ca href=\"/en/product/features/openflow/\"\u003EOpenflow\u003C/a\u003E objects\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENetwork Infrastructure\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAn AWS VPC with at least one subnet that has internet access\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EKnowledge Requirements\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EBasic understanding of AWS services (CloudFormation, DynamoDB, Kinesis Data Streams, EC2)\u003C/li\u003E\u003Cli\u003EFamiliarity with CloudFormation templates and parameters\u003C/li\u003E\u003Cli\u003EFamiliarity with Snowflake SQL and Snowsight UI\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAn Openflow deployment either on AWS BYOC or Snowflake VPC with Snowpark Container Services (SPCS) versions\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ERefer to this \u003Ca href=\"https://medium.com/@rahul.reddy.ai/your-step-by-step-practical-guide-to-setting-up-snowflake-openflow-on-aws-byoc-07e5b7be5056\"\u003Eblog\u003C/a\u003E to deploy Openflow on AWS BYOC.\u003C/li\u003E\u003Cli\u003EOpenflow - Snowflake Deployment, using Snowpark Container Services (SPCS), provides a streamlined and integrated solution for connectivity. Because SPCS is a self-contained service within Snowflake, it’s easy to deploy and manage and offers a convenient and cost-effective environment for running your data flows. Refer to this \u003Ca href=\"/en/developers/guides/getting-started-with-openflow-spcs/\"\u003Equickstart\u003C/a\u003E to get started.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EA Snowflake role that can access or create Openflow runtimes\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ERefer to this \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/setup-openflow\"\u003Edoc\u003C/a\u003E for more details.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n<!---------------------------->\n","\u003Ch2\u003EDeploy AWS Resources\u003C/h2\u003E\n","\u003Cp\u003EClick on this \u003Ca href=\"https://console.aws.amazon.com/cloudformation/home#/stacks/new?stackName=Openflow-DDB-CDC&templateURL=https://snowflake-corp-se-workshop.s3.us-west-1.amazonaws.com/Openflow_Dynamo_CDC/ddb-cft.yaml\"\u003Elink\u003C/a\u003E to start a CloudFormation template.\u003C/p\u003E\n","\u003Cp\u003EClick \u003Ccode\u003ENext\u003C/code\u003E, in the \u003Ccode\u003ESpecify stack details\u003C/code\u003E page, select a \u003Ccode\u003ESubnetId\u003C/code\u003E in the drop-down menu, this subnet will be used to deploy the EC2 instance. Note that this subnet must be a public subnet with egress to the internet. Also specify the \u003Ccode\u003EVpcId\u003C/code\u003E in the drop-down menu, make sure that you select a VPC that includes the subnet from above. Leave the other parameters as default and click \u003Ccode\u003ENext\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/cft-parameters.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EIn the \u003Ccode\u003EConfigure stack options\u003C/code\u003E page, check the box that says \u003Ccode\u003EI acknowledge that AWS CloudFormation might create IAM resources.\u003C/code\u003E and click \u003Ccode\u003ENext\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EClick \u003Ccode\u003ESubmit\u003C/code\u003E button to deploy the resources.\u003C/p\u003E\n","\u003Cp\u003EIn 5-10 minutes, the Cloudformation template finishes deploying the following AWS resources:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDynamoDB Table\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ETable name: Configurable (default: \u003Ccode\u003EInsuranceClaims\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003EPrimary key: \u003Ccode\u003Eclaim_id\u003C/code\u003E (String)\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EKinesis Data Stream\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EStream name: Configurable (default: \u003Ccode\u003EInsuranceClaimsStream\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003EShard count: 1\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EEC2 Jumphost\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ETo run a script to stream data into the DynamoDB table\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIAM Roles and Policies\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ETo ensure the created resources have appropriate permissions to carry out necessary tasks\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003ENext we are ready to connect to the EC2 instance to create the OpenSSL key pair used for authentication with Snowflake.\u003C/p\u003E\n","\u003Ch4\u003E1. Configure the Linux session for timeout and default shell\u003C/h4\u003E\n","\u003Cp\u003EIn this step we need to connect to the EC2 instance in order to ingest the real-time data.\u003C/p\u003E\n","\u003Cp\u003EGo to the AWS \u003Ca href=\"https://us-west-2.console.aws.amazon.com/systems-manager/home\"\u003ESystems Manager\u003C/a\u003E console in the same region where you set up the EC2 instance,\nClick \u003Ccode\u003ESession Manager\u003C/code\u003E on the left pane.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENext, we will set the preferred shell as bash.\u003C/p\u003E\n","\u003Cp\u003EClick the \u003Ccode\u003EPreferences\u003C/code\u003E tab.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.0.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick the \u003Ccode\u003EEdit\u003C/code\u003E button.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EGo to \u003Ccode\u003EGeneral preferences\u003C/code\u003E section, type in 60 minutes for idle session timeout value.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.1.5.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EFurther scroll down to \u003Ccode\u003ELinux shell profile\u003C/code\u003E section, and type in \u003Ccode\u003E/bin/bash\u003C/code\u003E before clicking \u003Ccode\u003ESave\u003C/code\u003E button.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.2.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch4\u003E2. Connect to the Linux EC2 instance console\u003C/h4\u003E\n","\u003Cp\u003ENow go back to the \u003Ccode\u003ESession\u003C/code\u003E tab and click the \u003Ccode\u003EStart session\u003C/code\u003E button.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-2.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENow you should see the EC2 instance created by the Cloudformation template under \u003Ccode\u003ETarget instances\u003C/code\u003E.\nIts name should be \u003Ccode\u003EMyEC2Instance\u003C/code\u003E, select it and click \u003Ccode\u003EStart session\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-3.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch4\u003E3. Create a key-pair to be used for authenticating with Snowflake\u003C/h4\u003E\n","\u003Cp\u003ECreate a key pair in AWS Session Manager console by executing the following commands. You will be prompted to give an encryption password(passphrase), remember this passphrase, you will need it later.\u003C/p\u003E\n","\u003Cp\u003E**Note, for better security, it is advised not to use an empty string as the passphrase\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-commandline\"\u003Ecd $HOME\nopenssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ESee below example screenshot:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/key-pair-sessionmgr-1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENext we will create a public key by running following commands. You will be prompted to type in the passphrase you used in above step.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003Eopenssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003Esee below example screenshot:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/key-pair-sessionmgr-2.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENext we will save the public and private key string in a correct format that we can use for configuration later.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003Egrep -v KEY rsa_key.pub | tr -d 'n' | awk '{print $1}' > pub.Key\ncat pub.Key\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003Esee below example screenshot:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/key-pair-sessionmgr-3.png\" alt=\"\"\u003E\u003C/p\u003E\n<!---------------------------->\n","\u003Ch2\u003ESetup Snowflake\u003C/h2\u003E\n","\u003Ch4\u003E1. Create role, schema and database\u003C/h4\u003E\n","\u003Cp\u003EFirst login to your Snowflake account as a power user with ACCOUNTADMIN role.\nThen run the following SQL commands in a worksheet to create a database, schema and the role that we will use in the lab.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Type in the username who has the ACCOUNTADMIN role\n-- This can be the username you picked when sign up for\n-- the Snowflake trial account\nSET USER = < username with ACCOUNTADMIN role >\n\u003C/code\u003E\u003C/pre\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Set default value for multiple variables\n-- For purpose of this workshop, it is recommended to use these defaults during the exercise to avoid errors\n-- You should change them after the workshop\nSET DB = 'CDC_DB';\nSET SCHEMA = 'CDC_SCHEMA';\nSET WH = 'CDC_WH';\nSET ROLE = 'CDC_RL';\n\nUSE ROLE ACCOUNTADMIN;\n\n-- CREATE ROLES\nCREATE OR REPLACE ROLE IDENTIFIER($ROLE);\n\n-- CREATE DATABASE AND WAREHOUSE\nCREATE DATABASE IF NOT EXISTS IDENTIFIER($DB);\nUSE IDENTIFIER($DB);\nCREATE SCHEMA IF NOT EXISTS IDENTIFIER($SCHEMA);\nCREATE OR REPLACE WAREHOUSE IDENTIFIER($WH) WITH WAREHOUSE_SIZE = 'SMALL';\n\n-- GRANTS\nGRANT CREATE WAREHOUSE ON ACCOUNT TO ROLE IDENTIFIER($ROLE);\nGRANT ROLE IDENTIFIER($ROLE) TO USER IDENTIFIER($USER);\nGRANT ROLE IDENTIFIER($ROLE) TO ROLE ACCOUNTADMIN;\nGRANT OWNERSHIP ON DATABASE IDENTIFIER($DB) TO ROLE IDENTIFIER($ROLE);\nGRANT OWNERSHIP ON SCHEMA IDENTIFIER($SCHEMA) TO ROLE IDENTIFIER($ROLE);\nGRANT USAGE ON WAREHOUSE IDENTIFIER($WH) TO ROLE IDENTIFIER($ROLE);\n\n-- SET DEFAULTS\nALTER USER IDENTIFIER($USER) SET DEFAULT_ROLE=$ROLE;\nALTER USER IDENTIFIER($USER) SET DEFAULT_WAREHOUSE=$WH;\n\n-- RUN FOLLOWING COMMANDS TO FIND YOUR ACCOUNT IDENTIFIER, WRITE IT DOWN FOR USE LATER\n-- IT WILL BE SOMETHING LIKE <organization_name>-<account_name>\n-- e.g. ykmxgak-wyb52636\n\nWITH HOSTLIST AS \n(SELECT * FROM TABLE(FLATTEN(INPUT => PARSE_JSON(SYSTEM$allowlist()))))\nSELECT REPLACE(VALUE:host,'.snowflakecomputing.com','') AS ACCOUNT_IDENTIFIER\nFROM HOSTLIST\nWHERE VALUE:type = 'SNOWFLAKE_DEPLOYMENT_REGIONLESS';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EPlease write down the Account Identifier, we will need it later.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/account-identifier.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch4\u003E2. Set Up Key Pair Authentication\u003C/h4\u003E\n","\u003Cp\u003ENext we need to configure the public key for the streaming user to access Snowflake programmatically.\u003C/p\u003E\n","\u003Cp\u003EIn the Snowflake worksheet, replace \u003Ccode\u003E< pubKey >\u003C/code\u003E with the content of the file \u003Ccode\u003E/home/ssm-user/pub.Key\u003C/code\u003E on the EC2 instance and execute the follow command in Snowflake SQL worksheet.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE ACCOUNTADMIN;\n\n-- Replace the username with the one (with ACCOUNTADMIN role) you used at the beggining in step 1 above\nALTER USER < username > SET RSA_PUBLIC_KEY='< pubKey >';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch4\u003E3. Set Up the Snowflake Tables\u003C/h4\u003E\n","\u003Cp\u003EConnect to your Snowflake account and create the CDC, event history and destination tables:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Use appropriate role, database, schema, and warehouse\nUSE ROLE IDENTIFIER($ROLE);\nUSE DATABASE IDENTIFIER($DB);\nUSE SCHEMA IDENTIFIER($SCHEMA);\nUSE WAREHOUSE IDENTIFIER($WH);\n\n-- Create the destination table (to be synchronized with the source DynamoDB table)\nCREATE OR REPLACE TABLE openflow_insclaim_dest_tbl (\n    eventName STRING,\n    eventCreationUnixTime STRING,\n    claimId STRING,\n    diagnosisCodes STRING,\n    dateOfService STRING,\n    totalCharge FLOAT,\n    procedureDetails STRING,\n    memberId STRING,\n    insurancePlan STRING,\n    patientZip INTEGER,\n    patientState STRING,\n    patientCity STRING,\n    patientStreet STRING,\n    patientGender VARCHAR(1),\n    patientDOB STRING,\n    patientLastName STRING,\n    patientPhone STRING,\n    patientFirstName STRING,\n    patientEmail STRING,\n    claimStatus STRING,\n    createdTimeStamp timestamp_ntz(9),\n    providerName STRING,\n    providerNPI STRING,\n    providerZip INTEGER,\n    providerState STRING,\n    providerCity STRING,\n    providerStreet STRING,\n    billSubmitDate STRING,\n    payerName STRING,\n    payerId STRING,\n    payerContactNumber STRING,\n    paymentStatus STRING\n);\n\n-- Create a event history table to track the changes being applied at the source\nCREATE OR REPLACE TABLE openflow_insClaim_event_hist_tbl LIKE openflow_insClaim_dest_tbl;\n\n-- Create a CDC operation table that holds the changes yet to be merged with the destination table\nCREATE OR REPLACE TABLE openflow_insClaim_cdc_tbl like openflow_insClaim_dest_tbl;\n\u003C/code\u003E\u003C/pre\u003E\n<!---------------------------->\n","\u003Ch2\u003ESetup Openflow Connector\u003C/h2\u003E\n","\u003Cp\u003EDownload the \u003Ca href=\"https://snowflake-corp-se-workshop.s3.us-west-1.amazonaws.com/Openflow_Dynamo_CDC/Openflow-DDB-CDC-connector.json\"\u003EOpenflow connector definition file\u003C/a\u003E and save it to your desktop.\u003C/p\u003E\n","\u003Ch4\u003E1. Import the connector definition file\u003C/h4\u003E\n","\u003Cp\u003EIn Snowsight, switch to the role that has access to Openflow runtimes (described in the \u003Ccode\u003EPrerequisites OR What You Will Need\u003C/code\u003E section above). Go to Openflow by clicking on \u003Ccode\u003EOpenflow\u003C/code\u003E in the \u003Ccode\u003EData\u003C/code\u003E drop-down menu in the Snowsight left pane.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-start.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick the \u003Ccode\u003ELaunch Openflow\u003C/code\u003E button located at the top-right corner to launch Openflow.\u003C/p\u003E\n","\u003Cp\u003EClick \u003Ccode\u003EView all\u003C/code\u003E in the Runtime tile.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-runtimes.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick on the runtime that is assigned to you by your Openflow administrator.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-canvas.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EDrag the processor group icon located at the top to the canvas, release mouse button, then click the browse button to import the json file (Openflow-DDB-CDC-connector.json) you just downloaded. The connector is now imported.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-processor-grp.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-imported-connector.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch4\u003E2. Configure parameters for the connector\u003C/h4\u003E\n","\u003Cp\u003ERight click anywhere on the connector and select \u003Ccode\u003EParameters\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-params.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThere are five parameters you will need to fill in. Leave the others as default. Click on the three dots and \u003Ccode\u003EEdit\u003C/code\u003E to add the values for each of them.\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAWS KEY ID\u003C/li\u003E\u003Cli\u003EAWS SECRET ACCESS KEY\u003C/li\u003E\u003Cli\u003ESNOWFLAKE ACCOUNT NAME: This is the Snowflake account identifier you wrote down previously\u003C/li\u003E\u003Cli\u003ESNOWFLAKE KEY PASSPHRASE: This is the Snowflake key passphrase you chose when creating the key pair with openssl\u003C/li\u003E\u003Cli\u003ESNOWFLAKE PRIVATE KEY: This is the content of the \u003Ccode\u003Ersa_key.p8\u003C/code\u003E file you created in the home directory on the EC2 instance.\u003C/li\u003E\u003Cli\u003ESNOWFLAKE USER: This is the username with ACCOUNTADMIN role when you setup Snowflake in previous step\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EOnce finished, click \u003Ccode\u003EApply\u003C/code\u003E and \u003Ccode\u003EClose\u003C/code\u003E to take effect.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-params-context.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick \u003Ccode\u003EBack to process group\u003C/code\u003E to return to the main canvas.\u003C/p\u003E\n","\u003Cp\u003ENow we are ready to start the Openflow connector. To do so, first right click on the connector and select \u003Ccode\u003EEnable\u003C/code\u003E. Next, right click on the connector again and select \u003Ccode\u003EEnable all controller services\u003C/code\u003E. Finally, right click on the connector and select \u003Ccode\u003EStart\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EDouble click anywhere on the connector, you will see all the processors that are used to make up the connector.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-all.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe pipeline is made up of Extract, Transform, Load and Merge stages:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EExtract: This is a processor \u003Ccode\u003EConsumeKinesisStream\u003C/code\u003E that listens to the CDC events in the Kinesis data stream and extract them.\u003C/li\u003E\u003Cli\u003ETransform: We use a couple of transformation processors (\u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/flattenjson\"\u003E\u003Ccode\u003EFlattenJson\u003C/code\u003E\u003C/a\u003E and \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/jolttransformjson\"\u003E\u003Ccode\u003EJoltTransformJSON\u003C/code\u003E\u003C/a\u003E) to transform the raw json into\na format that is consumable by the Snowflake tables. The raw json contains multi-level json structure and needs to be flattened and its long key names need to be renamed to shorter, descriptive column names in Snowflake.\u003C/li\u003E\u003Cli\u003ELoad: The \u003Ccode\u003EPutSnowpipeStreaming\u003C/code\u003E processors in this stage are used to stream the jsons into the CDC and event history tables we created previously.\u003C/li\u003E\u003Cli\u003EMerge: At this stage, we use the \u003Ccode\u003EExecuteSQLStatement\u003C/code\u003E processor to merge the changes held in the CDC table into the destination table to complete the synchronization.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003ENote, we also created the funnels to help us examine contents of the flow files at the Extract, Transformation and Merge stages so you can see the progress and json formats at different stages as the data passing through the pipeline.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-funnels.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EAt this point, we have successfully connected the Openflow connector to the upstream Kinesis data stream.\u003C/p\u003E\n","\u003Cp\u003EFor a list of all of the available Openflow processors, visit this \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/index\"\u003Edoc\u003C/a\u003E for more details.\u003C/p\u003E\n<!---------------------------->\n","\u003Ch2\u003EEnable \u003Ca href=\"https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html\"\u003EDynamoDB Streams\u003C/a\u003E\u003C/h2\u003E\n","\u003Cp\u003ENavigate to the \u003Ca href=\"https://console.aws.amazon.com/dynamodbv2/home?#tables\"\u003EDynamoDB Table Console\u003C/a\u003E and click \u003Ccode\u003EInsuranceClaims\u003C/code\u003E table.\u003C/p\u003E\n","\u003Cp\u003EClick on the tab that says \u003Ccode\u003EExports and streams\u003C/code\u003E at the top.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-exports-and-streams-1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EScroll all the way down to the bottom of the page and find the \u003Ccode\u003EAmazon Kinesis data stream details\u003C/code\u003E section, click \u003Ccode\u003ETurn on\u003C/code\u003E.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-exports-and-streams-2.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENext, you will be prompted to select the destination Kinesis data stream name to capture the CDC events. Go ahead and select \u003Ccode\u003EKDSInsuranceClaims\u003C/code\u003E as the destination stream, click \u003Ccode\u003ETurn on stream\u003C/code\u003E.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-exports-and-streams-3.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EIn a few seconds, the DynamoDB stream is enabled. You will see notification of success at the top of the page.\u003C/p\u003E\n<!---------------------------->\n","\u003Ch2\u003EChange Data Capture (CDC) In Action\u003C/h2\u003E\n","\u003Ch3\u003EIngest Claims to DynamoDB\u003C/h3\u003E\n","\u003Cp\u003ELet's ingest a few sample insurance claims into the source DynamoDB table. To do this, go back to the EC2 instance console in session manager and issue this command:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-command\"\u003Ecd $HOME\npython3 ingest_med_claims.py 20\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis will ingest 20 sample claims into the DynamoDB table and because these are new CDC events, so they will be captured by DynamoDB streams and get streamed into the Kinesis data stream followed by the Openflow pipeline.\u003C/p\u003E\n","\u003Cp\u003ELet's navigate to the \u003Ca href=\"https://console.aws.amazon.com/dynamodbv2/home?#tables\"\u003EDynamoDB Table Console\u003C/a\u003E and click on the \u003Ccode\u003EInsuranceClaims\u003C/code\u003E table, then click the \u003Ccode\u003EExplore table items\u003C/code\u003E button located at the top-right corner of the page. You should see 20 items have been inserted to the table. If you don't see them, just click the \u003Ccode\u003ERun\u003C/code\u003E button to refresh.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-explore.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENow, go to the Openflow canvas, you should notice that 20 items are also captured by Openflow and they are merged and landed in the destination table in Snowflake. You can right click anywhere on the canvas and select \u003Ccode\u003ERefresh\u003C/code\u003E to see the number of items in \u003Ccode\u003EQueue2\u003C/code\u003E keeps increasing until it hits 20.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-insert-20.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ETo verify, go to the worksheet in Snowsight and issue this SQL command:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- count and show rows in the destination table\nselect * from openflow_insclaim_dest_tbl;\nselect count(*) from openflow_insclaim_dest_tbl;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/worksheet-insert.png\" alt=\"\"\u003E\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- All the Insert events are captured in the event history table\nselect * from openflow_insclaim_event_hist_tbl where eventname='INSERT';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EModify Claim Status in DynamoDB\u003C/h3\u003E\n","\u003Cp\u003EIn this step, let's modify the claim status in the source DynamoDB table and see the change synchronized with the destination table in Snowflake thanks to the CDC operations by Openflow.\u003C/p\u003E\n","\u003Cp\u003EGo to the DynamoDB console, pick any claim whose status is \u003Ccode\u003EIn Review\u003C/code\u003E.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-modify-1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EModify the status from \u003Ccode\u003EIn Review\u003C/code\u003E to \u003Ccode\u003ERejected\u003C/code\u003E, then click \u003Ccode\u003ESave and close\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-modify-2.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EBecause this is a new CDC 'MODIFY' event, you will see the number in Queue1 and Queue2 in Openflow increased to 21 now.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-modify-21.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ETo verify, go to the worksheet in Snowsight and issue this SQL command:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003Eselect \n    eventName,\n    TO_TIMESTAMP(TO_NUMBER(eventCreationUnixTime) / 1000000) AS eventCreationUTC,\n    claimId, \n    claimStatus, \n    paymentStatus, \n    totalCharge, \n    insurancePlan,\n    memberId,\n    providerName\n  from openflow_insclaim_dest_tbl where eventname = 'MODIFY';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou can see the claim status has been changed from \u003Ccode\u003EIn Review\u003C/code\u003E to \u003Ccode\u003ERejected\u003C/code\u003E in the destination table too, this means the source DynamoDB and destination table are synchronized in real-time! Note that modification time stamp is also captured in the \u003Ccode\u003EEVENTCREATIONUTC\u003C/code\u003E column.\u003C/p\u003E\n","\u003Cp\u003EThe update is again logged in the event history table.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003Eselect \n    eventName,\n    TO_TIMESTAMP(TO_NUMBER(eventCreationUnixTime) / 1000000) AS eventCreationUTC,\n    claimId, \n    claimStatus, \n    paymentStatus, \n    totalCharge, \n    insurancePlan,\n    memberId,\n    providerName\n  from openflow_insclaim_event_hist_tbl where eventname = 'MODIFY' order by eventCreationUTC;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/worksheet-modify.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EDelete Claims from DynamoDB\u003C/h3\u003E\n","\u003Cp\u003ENow let's delete the claim we just modified by going to the DynamoDB console, check the claim and select \u003Ccode\u003EDelete items\u003C/code\u003E from the \u003Ccode\u003EActions\u003C/code\u003E drop-down menu and confirm.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-delete.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ESimilarly, because the claim deletion is a new CDC event, you will see the counters in Queue1 and Queue2 increased to 22 now.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-delete-22.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003ENow if you issue the following SQL query, the result should be empty because the claim has been deleted from the destination table too.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT *\nFROM openflow_insclaim_dest_tbl\n-- get the claim id from the event history table\nWHERE claimid IN (\n    SELECT claimid\n    FROM openflow_insclaim_event_hist_tbl\n    WHERE eventname = 'MODIFY'\n);\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAgain, the deletion event is captured in the event history table.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003Eselect \n    eventName,\n    TO_TIMESTAMP(TO_NUMBER(eventCreationUnixTime) / 1000000) AS eventCreationUTC,\n    claimId, \n    claimStatus, \n    paymentStatus, \n    totalCharge, \n    insurancePlan,\n    memberId,\n    providerName\n  from openflow_insclaim_event_hist_tbl where eventname = 'REMOVE' order by eventCreationUTC;\n\u003C/code\u003E\u003C/pre\u003E\n<!---------------------------->\n","\u003Ch2\u003ETransformed Data Across Pipeline\u003C/h2\u003E\n","\u003Cp\u003EYou can view the transformed json contents in various stages by right-clicking tags in the pipeline, and select \u003Ccode\u003EList queue\u003C/code\u003E\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-listqueue-1.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003Eclick on the 3 dots and select \u003Ccode\u003EDownload content\u003C/code\u003E and they will be saved to your computer.\n\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-listqueue-2.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EFeel free to compare these contents to see how the data is transformed by the \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/flattenjson\"\u003E\u003Ccode\u003EFlatJson\u003C/code\u003E\u003C/a\u003E and \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/jolttransformjson\"\u003E\u003Ccode\u003EJoltTransformJson\u003C/code\u003E\u003C/a\u003E processors.\u003C/p\u003E\n<!---------------------------->\n","\u003Ch2\u003EThe ExecuSQLCommand Processor\u003C/h2\u003E\n","\u003Cp\u003ELet's take a look at the \u003Ccode\u003EExecuteSQLStatement\u003C/code\u003E processor and see what SQL query it uses to merge the CDC events.\u003C/p\u003E\n","\u003Cp\u003ERight click on the \u003Ccode\u003EExecuteSQLStatement\u003C/code\u003E processor and select \u003Ccode\u003EView configuration\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-executesql.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick on the \u003Ccode\u003Eproperties\u003C/code\u003E tab at the top and click \u003Ccode\u003ESQL\u003C/code\u003E to expand the value, here you will see the SQL queries used to merge the CDC events.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-executesql-commands.png\" alt=\"\"\u003E\u003C/p\u003E\n","\u003Cp\u003EFor your reference, below is the SQL command used in the \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/executesqlstatement\"\u003EOpenflow ExecuSQLCommand processor\u003C/a\u003E to merge the events in the CDC table to destination table in Snowflake.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EBEGIN\n-- Create temporary table with all claimIds to be processed\nCREATE OR REPLACE TEMPORARY TABLE temp_claim_ids AS\nSELECT DISTINCT claimId \nFROM openflow_insclaim_cdc_tbl;\n\n-- Perform the merge operation\nMERGE INTO openflow_insclaim_dest_tbl tgt\n    USING openflow_insclaim_cdc_tbl src\n    ON tgt.claimId = src.claimId\n\n    -- Delete rows\n    WHEN MATCHED AND src.eventName = 'REMOVE' THEN DELETE\n\n    -- Update existing rows\n    WHEN MATCHED AND src.eventName = 'MODIFY'\n    THEN\n        UPDATE SET\n            tgt.eventName = src.eventName,\n            tgt.eventCreationUnixTime = src.eventCreationUnixTime,\n            tgt.claimId = src.claimId,\n            tgt.diagnosisCodes = src.diagnosisCodes,\n            tgt.dateOfService = src.dateOfService,\n            tgt.totalCharge = src.totalCharge,\n            tgt.procedureDetails = src.procedureDetails,\n            tgt.memberId = src.memberId,\n            tgt.insurancePlan = src.insurancePlan,\n            tgt.patientZip = src.patientZip,\n            tgt.patientState = src.patientState,\n            tgt.patientCity = src.patientCity,\n            tgt.patientStreet = src.patientStreet,\n            tgt.patientGender = src.patientGender,\n            tgt.patientDOB = src.patientDOB,\n            tgt.patientLastName = src.patientLastName,\n            tgt.patientPhone = src.patientPhone,\n            tgt.patientFirstName = src.patientFirstName,\n            tgt.patientEmail = src.patientEmail,\n            tgt.claimStatus = src.claimStatus,\n            tgt.createdTimeStamp = src.createdTimeStamp,\n            tgt.providerName = src.providerName,\n            tgt.providerNPI = src.providerNPI,\n            tgt.providerZip = src.providerZip,\n            tgt.providerState = src.providerState,\n            tgt.providerCity = src.providerCity,\n            tgt.providerStreet = src.providerStreet,\n            tgt.billSubmitDate = src.billSubmitDate,\n            tgt.payerName = src.payerName,\n            tgt.payerId = src.payerId,\n            tgt.payerContactNumber = src.payerContactNumber,\n            tgt.paymentStatus = src.paymentStatus\n\n    -- Insert new rows that don't exist in target_table\n    WHEN NOT MATCHED AND src.eventName = 'INSERT' THEN\n        INSERT (eventName, eventCreationUnixTime, claimId, diagnosisCodes, dateOfService, totalCharge, procedureDetails, memberId, insurancePlan, patientZip, patientState, patientCity, patientStreet, patientGender, patientDOB, patientLastName, patientPhone, patientFirstName, patientEmail, claimStatus, createdTimeStamp, providerName, providerNPI, providerZip, providerState, providerCity, providerStreet, billSubmitDate, payerName, payerId, payerContactNumber, paymentStatus)\n        VALUES (src.eventName, src.eventCreationUnixTime, src.claimId, src.diagnosisCodes, src.dateOfService, src.totalCharge, src.procedureDetails, src.memberId, src.insurancePlan, src.patientZip, src.patientState, src.patientCity, src.patientStreet, src.patientGender, src.patientDOB, src.patientLastName, src.patientPhone, src.patientFirstName, src.patientEmail, src.claimStatus, src.createdTimeStamp, src.providerName, src.providerNPI, src.providerZip, src.providerState, src.providerCity, src.providerStreet, src.billSubmitDate, src.payerName, src.payerId, src.payerContactNumber, src.paymentStatus);\n\n-- Delete processed records in the cdc table from temp table\nDELETE FROM openflow_insclaim_cdc_tbl \nWHERE claimId IN (SELECT claimId FROM temp_claim_ids);\n\nEND;\n\u003C/code\u003E\u003C/pre\u003E\n<!---------------------------->\n","\u003Ch2\u003ECleanup\u003C/h2\u003E\n","\u003Cp\u003EWhen you're done with the demo, you can delete all resources to avoid incurring charges:\u003C/p\u003E\n","\u003Ch3\u003E1. Delete the CloudFormation Stack\u003C/h3\u003E\n","\u003Cp\u003EUsing the AWS Management Console:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ENavigate to CloudFormation\u003C/li\u003E\u003Cli\u003ESelect your stack\u003C/li\u003E\u003Cli\u003EClick "Delete"\u003C/li\u003E\u003Cli\u003EConfirm the deletion\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EUsing the AWS CLI:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-bash\"\u003Eaws cloudformation delete-stack --stack-name Openflow-DDB-CDC\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003E2. Verify Resource Deletion\u003C/h3\u003E\n","\u003Cp\u003EEnsure that all resources have been deleted:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EEC2 instance\u003C/li\u003E\u003Cli\u003EDynamoDB table\u003C/li\u003E\u003Cli\u003EKinesis stream\u003C/li\u003E\u003Cli\u003EIAM roles and policies\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003E3. Clean Up Snowflake Resources (Optional)\u003C/h3\u003E\n","\u003Cp\u003EIf you no longer need the Snowflake tables:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE ACCOUNTADMIN;\n-- Drop Snowflake tables\nDROP TABLE IF EXISTS openflow_insclaim_dest_tbl;\nDROP TABLE IF EXISTS openflow_insclaim_cdc_tbl;\nDROP TABLE IF EXISTS openflow_insclaim_event_hist_tbl;\n-- Drop schema and database\nDROP SCHEMA CDC_SCHEMA;\nDROP DATABASE CDC_DB;\n\u003C/code\u003E\u003C/pre\u003E\n<!---------------------------->\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EIn this quickstart guide, you've built a complete Change Data Capture (CDC) pipeline that synchronizes healthcare insurance claims data between Amazon DynamoDB and Snowflake. This architecture leverages DynamoDB's strengths as a high-performance, scalable front-end database for real-time claims processing, while utilizing Snowflake's powerful analytics capabilities for complex reporting, data sharing, and long-term trend analysis. The Openflow connector serves as the critical bridge between these systems, ensuring that all changes (inserts, updates, and deletions) are captured and synchronized in near real-time.\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to set up and configure DynamoDB streams to capture change events\u003C/li\u003E\u003Cli\u003EHow to use Kinesis Data Streams as a transport layer for CDC events\u003C/li\u003E\u003Cli\u003EHow to configure and deploy an Openflow connector for real-time data integration\u003C/li\u003E\u003Cli\u003EHow to transform complex JSON data structures into analytics-ready formats\u003C/li\u003E\u003Cli\u003EHow to implement CDC operations (INSERT, MODIFY, REMOVE) with proper tracking\u003C/li\u003E\u003Cli\u003EHow to use Snowflake's MERGE operation for efficient data synchronization\u003C/li\u003E\u003Cli\u003EHow to maintain an audit trail of all data changes using event history tables\u003C/li\u003E\u003Cli\u003EBest practices for healthcare data integration across AWS and Snowflake\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EResources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/about\"\u003ESnowflake Openflow Documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/index\"\u003ESnowflake Openflow Processors\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/merge\"\u003ESnowflake MERGE Statement Documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html\"\u003EAmazon DynamoDB Streams Documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.aws.amazon.com/streams/latest/dev/introduction.html\"\u003EAmazon Kinesis Data Streams Documentation\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html\"\u003EAWS CloudFormation Documentation\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"title":"Streamlining Healthcare Claims Change Data Capture Processing Using Amazon DynamoDB and Snowflake OpenFlow",":items":{},":itemsOrder":[],"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\u003C!----------------------------\u003E\r\n## Overview\r\n\r\n### Overview\r\nIn a healthcare claims processing system, [Amazon DynamoDB](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Introduction.html) can serve as an effective front-end database due to its high scalability, low-latency performance, and schema flexibility. It allows real-time ingestion and access to diverse, evolving claim event data such as status changes, user interactions, or system-generated events without the constraints of a rigid relational schema. This is especially valuable in front-end applications where speed and adaptability are critical. On the back end, Snowflake complements DynamoDB by handling complex analytics, aggregations, data sharing and reporting. Claim data can be streamed in near real-time from DynamoDB into Snowflake via [Openflow](/en/product/features/openflow/) seamlessly, where advanced SQL queries, joins, and business intelligence tools can be applied to support audits, compliance checks, long-term trends and securely shared with teams across the globe. Together, this architecture balances speed and flexibility at the front with powerful analytics and data integrity at the back.\r\n\r\nThis guickstart will walk you through how to build CDC pipelines to synchronize the front-end DynamoDB and back-end Snowflake tables for processing real-time insurance claims\r\n\r\nBelow is a schematic diagram of the demo. The CDC events in DynamoDB are captured in a [Kinesis data stream](https://docs.aws.amazon.com/streams/latest/dev/key-concepts.html), we then use an Openflow connector to consume those events and they are streamed into a CDC table which holds the events yet to be merged with the destination table, while all historical events are loaded into the event history table for logging and tracking purposes. After the CDC events are merged, the source DynamoDB table and the destination Snowflake table are synchronized.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/demo-diagram.png)\r\n\r\n### What You Will Learn\r\n- How to set up Change Data Capture (CDC) between Amazon DynamoDB and Snowflake\r\n- How to configure and use Snowflake Openflow for real-time data synchronization\r\n- How to capture and process DynamoDB stream events using Kinesis Data Streams\r\n- How to transform semi-structured JSON data for analytics in Openflow\r\n- How to implement and monitor real-time CDC operations (INSERT, MODIFY, REMOVE)\r\n- Best practices for healthcare claims data processing in a hybrid architecture\r\n\r\n### What You will Build\r\n- A complete CDC pipeline that synchronizes healthcare insurance claims data between DynamoDB and Snowflake\r\n- An Openflow connector that consumes, transforms, and loads CDC events into Snowflake\r\n- A set of Snowflake tables for storing and tracking claim events, including:\r\n  - A destination table synchronized with the source DynamoDB table\r\n  - A CDC operations table for staging changes\r\n  - An event history table for auditing and tracking all data modifications\r\n- SQL merge operations that maintain data consistency across both systems\r\n\r\n### Prerequisites OR What You Will Need\r\nBefore proceeding with the quickstart, ensure you have:\r\n\r\n1. **Snowflake and AWS Account Access**\r\n   - A Snowflake account in one of the AWS commercial [regions](https://docs.snowflake.com/en/user-guide/intro-regions#label-na-general-regions). If you do not have one you can register for a [free trial account](https://signup.snowflake.com/?utm_cta=quickstart-insurance-claims-dynamodb-openflow-cdc).\r\n   - An AWS account with permissions to create the required resources using [Cloudformation](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html).\r\n   - Access to the AWS Management Console and [AWS CLI](https://docs.aws.amazon.com/cli/v1/userguide/cli-chap-configure.html) configured with required credentials.\r\n   - A Snowflake account with permissions to run queries and create [Openflow](/en/product/features/openflow/) objects\r\n\r\n2. **Network Infrastructure**\r\n   - An AWS VPC with at least one subnet that has internet access\r\n\r\n3. **Knowledge Requirements**\r\n   - Basic understanding of AWS services (CloudFormation, DynamoDB, Kinesis Data Streams, EC2)\r\n   - Familiarity with CloudFormation templates and parameters\r\n   - Familiarity with Snowflake SQL and Snowsight UI\r\n\r\n4. **An Openflow deployment either on AWS BYOC or Snowflake VPC with Snowpark Container Services (SPCS) versions**\r\n   - Refer to this [blog](https://medium.com/@rahul.reddy.ai/your-step-by-step-practical-guide-to-setting-up-snowflake-openflow-on-aws-byoc-07e5b7be5056) to deploy Openflow on AWS BYOC.\r\n   - Openflow - Snowflake Deployment, using Snowpark Container Services (SPCS), provides a streamlined and integrated solution for connectivity. Because SPCS is a self-contained service within Snowflake, it’s easy to deploy and manage and offers a convenient and cost-effective environment for running your data flows. Refer to this [quickstart](/en/developers/guides/getting-started-with-openflow-spcs/) to get started.\r\n\r\n5. **A Snowflake role that can access or create Openflow runtimes**\r\n   - Refer to this [doc](https://docs.snowflake.com/en/user-guide/data-integration/openflow/setup-openflow) for more details.\r\n\r\n\u003C!----------------------------\u003E\r\n## Deploy AWS Resources\r\n\r\nClick on this [link](https://console.aws.amazon.com/cloudformation/home#/stacks/new?stackName=Openflow-DDB-CDC&templateURL=https://snowflake-corp-se-workshop.s3.us-west-1.amazonaws.com/Openflow_Dynamo_CDC/ddb-cft.yaml) to start a CloudFormation template. \r\n\r\nClick `Next`, in the `Specify stack details` page, select a `SubnetId` in the drop-down menu, this subnet will be used to deploy the EC2 instance. Note that this subnet must be a public subnet with egress to the internet. Also specify the `VpcId` in the drop-down menu, make sure that you select a VPC that includes the subnet from above. Leave the other parameters as default and click `Next`.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/cft-parameters.png)\r\n\r\nIn the `Configure stack options` page, check the box that says `I acknowledge that AWS CloudFormation might create IAM resources.` and click `Next`. \r\n\r\nClick `Submit` button to deploy the resources.\r\n\r\nIn 5-10 minutes, the Cloudformation template finishes deploying the following AWS resources:\r\n\r\n1. **DynamoDB Table**\r\n   - Table name: Configurable (default: `InsuranceClaims`)\r\n   - Primary key: `claim_id` (String)\r\n\r\n2. **Kinesis Data Stream**\r\n   - Stream name: Configurable (default: `InsuranceClaimsStream`)\r\n   - Shard count: 1\r\n\r\n3. **EC2 Jumphost**\r\n   - To run a script to stream data into the DynamoDB table\r\n\r\n4. **IAM Roles and Policies**\r\n   - To ensure the created resources have appropriate permissions to carry out necessary tasks\r\n\r\n\r\nNext we are ready to connect to the EC2 instance to create the OpenSSL key pair used for authentication with Snowflake.\r\n\r\n#### 1. Configure the Linux session for timeout and default shell\r\n\r\nIn this step we need to connect to the EC2 instance in order to ingest the real-time data.\r\n\r\nGo to the AWS [Systems Manager](https://us-west-2.console.aws.amazon.com/systems-manager/home) console in the same region where you set up the EC2 instance,\r\nClick `Session Manager` on the left pane.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.png)\r\n\r\nNext, we will set the preferred shell as bash.\r\n\r\nClick the `Preferences` tab.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.0.png)\r\n\r\nClick the `Edit` button.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.1.png)\r\n\r\nGo to `General preferences` section, type in 60 minutes for idle session timeout value.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.1.5.png)\r\n\r\nFurther scroll down to `Linux shell profile` section, and type in `/bin/bash` before clicking `Save` button.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-1.2.png)\r\n\r\n\r\n#### 2. Connect to the Linux EC2 instance console\r\nNow go back to the `Session` tab and click the `Start session` button.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-2.png)\r\n\r\nNow you should see the EC2 instance created by the Cloudformation template under `Target instances`.\r\nIts name should be `MyEC2Instance`, select it and click `Start session`.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/session-mgr-3.png)\r\n\r\n#### 3. Create a key-pair to be used for authenticating with Snowflake\r\nCreate a key pair in AWS Session Manager console by executing the following commands. You will be prompted to give an encryption password(passphrase), remember this passphrase, you will need it later.\r\n\r\n**Note, for better security, it is advised not to use an empty string as the passphrase\r\n\r\n```commandline\r\ncd $HOME\r\nopenssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8\r\n```\r\nSee below example screenshot:\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/key-pair-sessionmgr-1.png)\r\n\r\nNext we will create a public key by running following commands. You will be prompted to type in the passphrase you used in above step.\r\n```\r\nopenssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub\r\n```\r\nsee below example screenshot:\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/key-pair-sessionmgr-2.png)\r\n\r\nNext we will save the public and private key string in a correct format that we can use for configuration later.\r\n```\r\ngrep -v KEY rsa_key.pub | tr -d 'n' | awk '{print $1}' \u003E pub.Key\r\ncat pub.Key\r\n```\r\nsee below example screenshot:\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/key-pair-sessionmgr-3.png)\r\n\r\n\u003C!----------------------------\u003E\r\n## Setup Snowflake\r\n\r\n#### 1. Create role, schema and database\r\nFirst login to your Snowflake account as a power user with ACCOUNTADMIN role. \r\nThen run the following SQL commands in a worksheet to create a database, schema and the role that we will use in the lab.\r\n\r\n```sql\r\n-- Type in the username who has the ACCOUNTADMIN role\r\n-- This can be the username you picked when sign up for\r\n-- the Snowflake trial account\r\nSET USER = \u003C username with ACCOUNTADMIN role \u003E\r\n```\r\n\r\n```sql\r\n-- Set default value for multiple variables\r\n-- For purpose of this workshop, it is recommended to use these defaults during the exercise to avoid errors\r\n-- You should change them after the workshop\r\nSET DB = 'CDC_DB';\r\nSET SCHEMA = 'CDC_SCHEMA';\r\nSET WH = 'CDC_WH';\r\nSET ROLE = 'CDC_RL';\r\n\r\nUSE ROLE ACCOUNTADMIN;\r\n\r\n-- CREATE ROLES\r\nCREATE OR REPLACE ROLE IDENTIFIER($ROLE);\r\n\r\n-- CREATE DATABASE AND WAREHOUSE\r\nCREATE DATABASE IF NOT EXISTS IDENTIFIER($DB);\r\nUSE IDENTIFIER($DB);\r\nCREATE SCHEMA IF NOT EXISTS IDENTIFIER($SCHEMA);\r\nCREATE OR REPLACE WAREHOUSE IDENTIFIER($WH) WITH WAREHOUSE_SIZE = 'SMALL';\r\n\r\n-- GRANTS\r\nGRANT CREATE WAREHOUSE ON ACCOUNT TO ROLE IDENTIFIER($ROLE);\r\nGRANT ROLE IDENTIFIER($ROLE) TO USER IDENTIFIER($USER);\r\nGRANT ROLE IDENTIFIER($ROLE) TO ROLE ACCOUNTADMIN;\r\nGRANT OWNERSHIP ON DATABASE IDENTIFIER($DB) TO ROLE IDENTIFIER($ROLE);\r\nGRANT OWNERSHIP ON SCHEMA IDENTIFIER($SCHEMA) TO ROLE IDENTIFIER($ROLE);\r\nGRANT USAGE ON WAREHOUSE IDENTIFIER($WH) TO ROLE IDENTIFIER($ROLE);\r\n\r\n-- SET DEFAULTS\r\nALTER USER IDENTIFIER($USER) SET DEFAULT_ROLE=$ROLE;\r\nALTER USER IDENTIFIER($USER) SET DEFAULT_WAREHOUSE=$WH;\r\n\r\n-- RUN FOLLOWING COMMANDS TO FIND YOUR ACCOUNT IDENTIFIER, WRITE IT DOWN FOR USE LATER\r\n-- IT WILL BE SOMETHING LIKE \u003Corganization_name\u003E-\u003Caccount_name\u003E\r\n-- e.g. ykmxgak-wyb52636\r\n\r\nWITH HOSTLIST AS \r\n(SELECT * FROM TABLE(FLATTEN(INPUT =\u003E PARSE_JSON(SYSTEM$allowlist()))))\r\nSELECT REPLACE(VALUE:host,'.snowflakecomputing.com','') AS ACCOUNT_IDENTIFIER\r\nFROM HOSTLIST\r\nWHERE VALUE:type = 'SNOWFLAKE_DEPLOYMENT_REGIONLESS';\r\n```\r\n\r\nPlease write down the Account Identifier, we will need it later.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/account-identifier.png)\r\n\r\n#### 2. Set Up Key Pair Authentication\r\nNext we need to configure the public key for the streaming user to access Snowflake programmatically.\r\n\r\nIn the Snowflake worksheet, replace `\u003C pubKey \u003E` with the content of the file `/home/ssm-user/pub.Key` on the EC2 instance and execute the follow command in Snowflake SQL worksheet.\r\n\r\n```sql\r\nUSE ROLE ACCOUNTADMIN;\r\n\r\n-- Replace the username with the one (with ACCOUNTADMIN role) you used at the beggining in step 1 above\r\nALTER USER \u003C username \u003E SET RSA_PUBLIC_KEY='\u003C pubKey \u003E';\r\n```\r\n\r\n#### 3. Set Up the Snowflake Tables\r\n\r\nConnect to your Snowflake account and create the CDC, event history and destination tables:\r\n\r\n```sql\r\n-- Use appropriate role, database, schema, and warehouse\r\nUSE ROLE IDENTIFIER($ROLE);\r\nUSE DATABASE IDENTIFIER($DB);\r\nUSE SCHEMA IDENTIFIER($SCHEMA);\r\nUSE WAREHOUSE IDENTIFIER($WH);\r\n\r\n-- Create the destination table (to be synchronized with the source DynamoDB table)\r\nCREATE OR REPLACE TABLE openflow_insclaim_dest_tbl (\r\n    eventName STRING,\r\n    eventCreationUnixTime STRING,\r\n    claimId STRING,\r\n    diagnosisCodes STRING,\r\n    dateOfService STRING,\r\n    totalCharge FLOAT,\r\n    procedureDetails STRING,\r\n    memberId STRING,\r\n    insurancePlan STRING,\r\n    patientZip INTEGER,\r\n    patientState STRING,\r\n    patientCity STRING,\r\n    patientStreet STRING,\r\n    patientGender VARCHAR(1),\r\n    patientDOB STRING,\r\n    patientLastName STRING,\r\n    patientPhone STRING,\r\n    patientFirstName STRING,\r\n    patientEmail STRING,\r\n    claimStatus STRING,\r\n    createdTimeStamp timestamp_ntz(9),\r\n    providerName STRING,\r\n    providerNPI STRING,\r\n    providerZip INTEGER,\r\n    providerState STRING,\r\n    providerCity STRING,\r\n    providerStreet STRING,\r\n    billSubmitDate STRING,\r\n    payerName STRING,\r\n    payerId STRING,\r\n    payerContactNumber STRING,\r\n    paymentStatus STRING\r\n);\r\n\r\n-- Create a event history table to track the changes being applied at the source\r\nCREATE OR REPLACE TABLE openflow_insClaim_event_hist_tbl LIKE openflow_insClaim_dest_tbl;\r\n\r\n-- Create a CDC operation table that holds the changes yet to be merged with the destination table\r\nCREATE OR REPLACE TABLE openflow_insClaim_cdc_tbl like openflow_insClaim_dest_tbl;\r\n```\r\n\r\n\u003C!----------------------------\u003E\r\n## Setup Openflow Connector\r\n\r\n Download the [Openflow connector definition file](https://snowflake-corp-se-workshop.s3.us-west-1.amazonaws.com/Openflow_Dynamo_CDC/Openflow-DDB-CDC-connector.json) and save it to your desktop.\r\n\r\n#### 1. Import the connector definition file\r\nIn Snowsight, switch to the role that has access to Openflow runtimes (described in the `Prerequisites OR What You Will Need` section above). Go to Openflow by clicking on `Openflow` in the `Data` drop-down menu in the Snowsight left pane.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-start.png)\r\n\r\nClick the `Launch Openflow` button located at the top-right corner to launch Openflow.\r\n\r\nClick `View all` in the Runtime tile.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-runtimes.png)\r\n\r\nClick on the runtime that is assigned to you by your Openflow administrator.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-canvas.png)\r\n\r\nDrag the processor group icon located at the top to the canvas, release mouse button, then click the browse button to import the json file (Openflow-DDB-CDC-connector.json) you just downloaded. The connector is now imported.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-processor-grp.png)\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-imported-connector.png)\r\n\r\n\r\n#### 2. Configure parameters for the connector\r\n\r\nRight click anywhere on the connector and select `Parameters`.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-params.png)\r\n\r\nThere are five parameters you will need to fill in. Leave the others as default. Click on the three dots and `Edit` to add the values for each of them.\r\n\r\n-  AWS KEY ID\r\n-  AWS SECRET ACCESS KEY\r\n-  SNOWFLAKE ACCOUNT NAME: This is the Snowflake account identifier you wrote down previously\r\n-  SNOWFLAKE KEY PASSPHRASE: This is the Snowflake key passphrase you chose when creating the key pair with openssl\r\n-  SNOWFLAKE PRIVATE KEY: This is the content of the `rsa_key.p8` file you created in the home directory on the EC2 instance.\r\n- SNOWFLAKE USER: This is the username with ACCOUNTADMIN role when you setup Snowflake in previous step\r\n\r\nOnce finished, click `Apply` and `Close` to take effect.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-params-context.png)\r\n\r\nClick `Back to process group` to return to the main canvas.\r\n\r\nNow we are ready to start the Openflow connector. To do so, first right click on the connector and select `Enable`. Next, right click on the connector again and select `Enable all controller services`. Finally, right click on the connector and select `Start`.\r\n\r\nDouble click anywhere on the connector, you will see all the processors that are used to make up the connector.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-all.png)\r\n\r\nThe pipeline is made up of Extract, Transform, Load and Merge stages:\r\n\r\n- Extract: This is a processor `ConsumeKinesisStream` that listens to the CDC events in the Kinesis data stream and extract them.\r\n- Transform: We use a couple of transformation processors ([`FlattenJson`](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/flattenjson) and [`JoltTransformJSON`](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/jolttransformjson)) to transform the raw json into \r\na format that is consumable by the Snowflake tables. The raw json contains multi-level json structure and needs to be flattened and its long key names need to be renamed to shorter, descriptive column names in Snowflake.\r\n- Load: The `PutSnowpipeStreaming` processors in this stage are used to stream the jsons into the CDC and event history tables we created previously.\r\n- Merge: At this stage, we use the `ExecuteSQLStatement` processor to merge the changes held in the CDC table into the destination table to complete the synchronization.\r\n\r\nNote, we also created the funnels to help us examine contents of the flow files at the Extract, Transformation and Merge stages so you can see the progress and json formats at different stages as the data passing through the pipeline.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-funnels.png)\r\n\r\nAt this point, we have successfully connected the Openflow connector to the upstream Kinesis data stream.\r\n\r\nFor a list of all of the available Openflow processors, visit this [doc](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/index) for more details.\r\n\r\n\u003C!----------------------------\u003E\r\n## Enable [DynamoDB Streams](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html)\r\n\r\nNavigate to the [DynamoDB Table Console](https://console.aws.amazon.com/dynamodbv2/home?#tables) and click `InsuranceClaims` table.\r\n\r\nClick on the tab that says `Exports and streams` at the top.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-exports-and-streams-1.png)\r\n\r\nScroll all the way down to the bottom of the page and find the `Amazon Kinesis data stream details` section, click `Turn on`.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-exports-and-streams-2.png)\r\n\r\nNext, you will be prompted to select the destination Kinesis data stream name to capture the CDC events. Go ahead and select `KDSInsuranceClaims` as the destination stream, click `Turn on stream`.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-exports-and-streams-3.png)\r\n\r\nIn a few seconds, the DynamoDB stream is enabled. You will see notification of success at the top of the page.\r\n\r\n\u003C!----------------------------\u003E\r\n## Change Data Capture (CDC) In Action\r\n\r\n### Ingest Claims to DynamoDB \r\nLet's ingest a few sample insurance claims into the source DynamoDB table. To do this, go back to the EC2 instance console in session manager and issue this command:\r\n\r\n```command\r\ncd $HOME\r\npython3 ingest_med_claims.py 20\r\n```\r\n\r\nThis will ingest 20 sample claims into the DynamoDB table and because these are new CDC events, so they will be captured by DynamoDB streams and get streamed into the Kinesis data stream followed by the Openflow pipeline. \r\n\r\nLet's navigate to the [DynamoDB Table Console](https://console.aws.amazon.com/dynamodbv2/home?#tables) and click on the `InsuranceClaims` table, then click the `Explore table items` button located at the top-right corner of the page. You should see 20 items have been inserted to the table. If you don't see them, just click the `Run` button to refresh.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-explore.png)\r\n\r\nNow, go to the Openflow canvas, you should notice that 20 items are also captured by Openflow and they are merged and landed in the destination table in Snowflake. You can right click anywhere on the canvas and select `Refresh` to see the number of items in `Queue2` keeps increasing until it hits 20.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-insert-20.png)\r\n\r\nTo verify, go to the worksheet in Snowsight and issue this SQL command:\r\n\r\n```sql\r\n-- count and show rows in the destination table\r\nselect * from openflow_insclaim_dest_tbl;\r\nselect count(*) from openflow_insclaim_dest_tbl;\r\n```\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/worksheet-insert.png)\r\n\r\n```sql\r\n-- All the Insert events are captured in the event history table\r\nselect * from openflow_insclaim_event_hist_tbl where eventname='INSERT';\r\n```\r\n\r\n### Modify Claim Status in DynamoDB\r\nIn this step, let's modify the claim status in the source DynamoDB table and see the change synchronized with the destination table in Snowflake thanks to the CDC operations by Openflow.\r\n\r\nGo to the DynamoDB console, pick any claim whose status is `In Review`.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-modify-1.png)\r\n\r\nModify the status from `In Review` to `Rejected`, then click `Save and close`.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-modify-2.png)\r\n\r\nBecause this is a new CDC 'MODIFY' event, you will see the number in Queue1 and Queue2 in Openflow increased to 21 now.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-modify-21.png)\r\n\r\nTo verify, go to the worksheet in Snowsight and issue this SQL command:\r\n\r\n```sql\r\nselect \r\n    eventName,\r\n    TO_TIMESTAMP(TO_NUMBER(eventCreationUnixTime) / 1000000) AS eventCreationUTC,\r\n    claimId, \r\n    claimStatus, \r\n    paymentStatus, \r\n    totalCharge, \r\n    insurancePlan,\r\n    memberId,\r\n    providerName\r\n  from openflow_insclaim_dest_tbl where eventname = 'MODIFY';\r\n```\r\nYou can see the claim status has been changed from `In Review` to `Rejected` in the destination table too, this means the source DynamoDB and destination table are synchronized in real-time! Note that modification time stamp is also captured in the `EVENTCREATIONUTC` column.\r\n\r\nThe update is again logged in the event history table.\r\n```sql\r\nselect \r\n    eventName,\r\n    TO_TIMESTAMP(TO_NUMBER(eventCreationUnixTime) / 1000000) AS eventCreationUTC,\r\n    claimId, \r\n    claimStatus, \r\n    paymentStatus, \r\n    totalCharge, \r\n    insurancePlan,\r\n    memberId,\r\n    providerName\r\n  from openflow_insclaim_event_hist_tbl where eventname = 'MODIFY' order by eventCreationUTC;\r\n```\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/worksheet-modify.png)\r\n\r\n\r\n### Delete Claims from DynamoDB\r\nNow let's delete the claim we just modified by going to the DynamoDB console, check the claim and select `Delete items` from the `Actions` drop-down menu and confirm.\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/ddb-delete.png)\r\n\r\nSimilarly, because the claim deletion is a new CDC event, you will see the counters in Queue1 and Queue2 increased to 22 now.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-delete-22.png)\r\n\r\nNow if you issue the following SQL query, the result should be empty because the claim has been deleted from the destination table too.\r\n\r\n```sql\r\nSELECT *\r\nFROM openflow_insclaim_dest_tbl\r\n-- get the claim id from the event history table\r\nWHERE claimid IN (\r\n    SELECT claimid\r\n    FROM openflow_insclaim_event_hist_tbl\r\n    WHERE eventname = 'MODIFY'\r\n);\r\n```\r\n\r\nAgain, the deletion event is captured in the event history table.\r\n```sql\r\nselect \r\n    eventName,\r\n    TO_TIMESTAMP(TO_NUMBER(eventCreationUnixTime) / 1000000) AS eventCreationUTC,\r\n    claimId, \r\n    claimStatus, \r\n    paymentStatus, \r\n    totalCharge, \r\n    insurancePlan,\r\n    memberId,\r\n    providerName\r\n  from openflow_insclaim_event_hist_tbl where eventname = 'REMOVE' order by eventCreationUTC;\r\n```\r\n\r\n\u003C!----------------------------\u003E\r\n## Transformed Data Across Pipeline\r\n\r\nYou can view the transformed json contents in various stages by right-clicking tags in the pipeline, and select `List queue`\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-listqueue-1.png)\r\n\r\nclick on the 3 dots and select `Download content` and they will be saved to your computer. \r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-listqueue-2.png)\r\n\r\nFeel free to compare these contents to see how the data is transformed by the [`FlatJson`](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/flattenjson) and [`JoltTransformJson`](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/jolttransformjson) processors.\r\n\r\n\u003C!----------------------------\u003E\r\n## The ExecuSQLCommand Processor\r\n\r\nLet's take a look at the `ExecuteSQLStatement` processor and see what SQL query it uses to merge the CDC events.\r\n\r\nRight click on the `ExecuteSQLStatement` processor and select `View configuration`.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-executesql.png)\r\n\r\nClick on the `properties` tab at the top and click `SQL` to expand the value, here you will see the SQL queries used to merge the CDC events.\r\n\r\n![](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/streamline-healthcare-cdc-ddb-and-openflow/openflow-executesql-commands.png)\r\n\r\nFor your reference, below is the SQL command used in the [Openflow ExecuSQLCommand processor](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/executesqlstatement) to merge the events in the CDC table to destination table in Snowflake.\r\n\r\n```sql\r\nBEGIN\r\n-- Create temporary table with all claimIds to be processed\r\nCREATE OR REPLACE TEMPORARY TABLE temp_claim_ids AS\r\nSELECT DISTINCT claimId \r\nFROM openflow_insclaim_cdc_tbl;\r\n\r\n-- Perform the merge operation\r\nMERGE INTO openflow_insclaim_dest_tbl tgt\r\n    USING openflow_insclaim_cdc_tbl src\r\n    ON tgt.claimId = src.claimId\r\n\r\n    -- Delete rows\r\n    WHEN MATCHED AND src.eventName = 'REMOVE' THEN DELETE\r\n\r\n    -- Update existing rows\r\n    WHEN MATCHED AND src.eventName = 'MODIFY'\r\n    THEN\r\n        UPDATE SET\r\n            tgt.eventName = src.eventName,\r\n            tgt.eventCreationUnixTime = src.eventCreationUnixTime,\r\n            tgt.claimId = src.claimId,\r\n            tgt.diagnosisCodes = src.diagnosisCodes,\r\n            tgt.dateOfService = src.dateOfService,\r\n            tgt.totalCharge = src.totalCharge,\r\n            tgt.procedureDetails = src.procedureDetails,\r\n            tgt.memberId = src.memberId,\r\n            tgt.insurancePlan = src.insurancePlan,\r\n            tgt.patientZip = src.patientZip,\r\n            tgt.patientState = src.patientState,\r\n            tgt.patientCity = src.patientCity,\r\n            tgt.patientStreet = src.patientStreet,\r\n            tgt.patientGender = src.patientGender,\r\n            tgt.patientDOB = src.patientDOB,\r\n            tgt.patientLastName = src.patientLastName,\r\n            tgt.patientPhone = src.patientPhone,\r\n            tgt.patientFirstName = src.patientFirstName,\r\n            tgt.patientEmail = src.patientEmail,\r\n            tgt.claimStatus = src.claimStatus,\r\n            tgt.createdTimeStamp = src.createdTimeStamp,\r\n            tgt.providerName = src.providerName,\r\n            tgt.providerNPI = src.providerNPI,\r\n            tgt.providerZip = src.providerZip,\r\n            tgt.providerState = src.providerState,\r\n            tgt.providerCity = src.providerCity,\r\n            tgt.providerStreet = src.providerStreet,\r\n            tgt.billSubmitDate = src.billSubmitDate,\r\n            tgt.payerName = src.payerName,\r\n            tgt.payerId = src.payerId,\r\n            tgt.payerContactNumber = src.payerContactNumber,\r\n            tgt.paymentStatus = src.paymentStatus\r\n\r\n    -- Insert new rows that don't exist in target_table\r\n    WHEN NOT MATCHED AND src.eventName = 'INSERT' THEN\r\n        INSERT (eventName, eventCreationUnixTime, claimId, diagnosisCodes, dateOfService, totalCharge, procedureDetails, memberId, insurancePlan, patientZip, patientState, patientCity, patientStreet, patientGender, patientDOB, patientLastName, patientPhone, patientFirstName, patientEmail, claimStatus, createdTimeStamp, providerName, providerNPI, providerZip, providerState, providerCity, providerStreet, billSubmitDate, payerName, payerId, payerContactNumber, paymentStatus)\r\n        VALUES (src.eventName, src.eventCreationUnixTime, src.claimId, src.diagnosisCodes, src.dateOfService, src.totalCharge, src.procedureDetails, src.memberId, src.insurancePlan, src.patientZip, src.patientState, src.patientCity, src.patientStreet, src.patientGender, src.patientDOB, src.patientLastName, src.patientPhone, src.patientFirstName, src.patientEmail, src.claimStatus, src.createdTimeStamp, src.providerName, src.providerNPI, src.providerZip, src.providerState, src.providerCity, src.providerStreet, src.billSubmitDate, src.payerName, src.payerId, src.payerContactNumber, src.paymentStatus);\r\n\r\n-- Delete processed records in the cdc table from temp table\r\nDELETE FROM openflow_insclaim_cdc_tbl \r\nWHERE claimId IN (SELECT claimId FROM temp_claim_ids);\r\n\r\nEND;\r\n```\r\n\r\n\u003C!----------------------------\u003E\r\n## Cleanup\r\n\r\nWhen you're done with the demo, you can delete all resources to avoid incurring charges:\r\n\r\n### 1. Delete the CloudFormation Stack\r\n\r\nUsing the AWS Management Console:\r\n1. Navigate to CloudFormation\r\n2. Select your stack\r\n3. Click \"Delete\"\r\n4. Confirm the deletion\r\n\r\nUsing the AWS CLI:\r\n\r\n```bash\r\naws cloudformation delete-stack --stack-name Openflow-DDB-CDC\r\n```\r\n\r\n### 2. Verify Resource Deletion\r\n\r\nEnsure that all resources have been deleted:\r\n- EC2 instance\r\n- DynamoDB table\r\n- Kinesis stream\r\n- IAM roles and policies\r\n\r\n### 3. Clean Up Snowflake Resources (Optional)\r\n\r\nIf you no longer need the Snowflake tables:\r\n\r\n```sql\r\nUSE ROLE ACCOUNTADMIN;\r\n-- Drop Snowflake tables\r\nDROP TABLE IF EXISTS openflow_insclaim_dest_tbl;\r\nDROP TABLE IF EXISTS openflow_insclaim_cdc_tbl;\r\nDROP TABLE IF EXISTS openflow_insclaim_event_hist_tbl;\r\n-- Drop schema and database\r\nDROP SCHEMA CDC_SCHEMA;\r\nDROP DATABASE CDC_DB;\r\n```\r\n\r\n\u003C!----------------------------\u003E\r\n## Conclusion And Resources \r\n\r\n### Overview\r\nIn this quickstart guide, you've built a complete Change Data Capture (CDC) pipeline that synchronizes healthcare insurance claims data between Amazon DynamoDB and Snowflake. This architecture leverages DynamoDB's strengths as a high-performance, scalable front-end database for real-time claims processing, while utilizing Snowflake's powerful analytics capabilities for complex reporting, data sharing, and long-term trend analysis. The Openflow connector serves as the critical bridge between these systems, ensuring that all changes (inserts, updates, and deletions) are captured and synchronized in near real-time.\r\n\r\n### What You Learned\r\n- How to set up and configure DynamoDB streams to capture change events\r\n- How to use Kinesis Data Streams as a transport layer for CDC events\r\n- How to configure and deploy an Openflow connector for real-time data integration\r\n- How to transform complex JSON data structures into analytics-ready formats\r\n- How to implement CDC operations (INSERT, MODIFY, REMOVE) with proper tracking\r\n- How to use Snowflake's MERGE operation for efficient data synchronization\r\n- How to maintain an audit trail of all data changes using event history tables\r\n- Best practices for healthcare data integration across AWS and Snowflake\r\n\r\n### Resources\r\n- [Snowflake Openflow Documentation](https://docs.snowflake.com/en/user-guide/data-integration/openflow/about)\r\n- [Snowflake Openflow Processors](https://docs.snowflake.com/en/user-guide/data-integration/openflow/processors/index)\r\n- [Snowflake MERGE Statement Documentation](https://docs.snowflake.com/en/sql-reference/sql/merge)\r\n- [Amazon DynamoDB Streams Documentation](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html)\r\n- [Amazon Kinesis Data Streams Documentation](https://docs.aws.amazon.com/streams/latest/dev/introduction.html)\r\n- [AWS CloudFormation Documentation](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html)",":type":"text/x-markdown","multiValue":false},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image",":type":"text/plain","multiValue":false}},"isDeveloperGuidesPage":false,":type":"snowflake-site/components/contentfragment","model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-4545433c7d","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-4e04ba57a9",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-ff68356ad8","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2025-10-07",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-9790ee1aa7","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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