{"id":3483,"date":"2023-04-12T15:33:22","date_gmt":"2023-04-12T15:33:22","guid":{"rendered":"https:\/\/quebit.com\/askquebit\/integrating-snowflake-and-ibm-planning-analytics\/"},"modified":"2026-01-16T17:20:35","modified_gmt":"2026-01-16T17:20:35","slug":"integrating-snowflake-and-ibm-planning-analytics","status":"publish","type":"post","link":"https:\/\/quebit.com\/askquebit\/integrating-snowflake-and-ibm-planning-analytics\/","title":{"rendered":"How Do I Integrate Snowflake Data with IBM Planning Analytics Using ODBC and TurboIntegrator?"},"content":{"rendered":"

In another post<\/a> I explored how easy it is to access cloud-based Snowflake, create a database, define and then load a table with data from a local file. In this post, I investigate the steps required to integrate some Snowflake data with IBM Planning Analytics (TM1). The steps will include:<\/p>\n

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  1. Configure an ODBC Data source on an MS Windows machine<\/li>\n
  2. Launching Planning Analytics Workspace on a client machine<\/li>\n
  3. Using Planning Analytics Workspace to create a TurboIntegrator process that accesses Snowflake data<\/li>\n<\/ol>\n

    An ETL Integration Approach<\/strong><\/p>\n

    TurboIntegrator<\/em><\/strong><\/a> is the \u201cextract, transform and load\u201d (or \u201cETL\u201d) tool provided by IBM Planning Analytics. TurboIntegrator allows you to create simple or complex processes to extract<\/em><\/strong> data from a data source \u2013 either a cube view or external system \u2013 transform<\/em><\/strong> it as needed and then load<\/em><\/strong> or otherwise use that data to update existing or newly created objects within a TM1\/Planning Analytics model.<\/p>\n

    The steps for building a process to use a TM1 view as a data source are similar to those used to define and use any other data source, except that you first build a view of data that is specifically designed for import. The steps to create a process that executes a SQL command to query a database<\/em> (or execute other SQL tasks) are the same but require setting up an Open Database Connectivity Data source Name (or ODBC DSN<\/a>) configured to access the external data.<\/p>\n

    Creating the ODBC DSN<\/strong><\/p>\n

    Assuming we will use the database and the specific table I created in my last post (millers_motorcycles_db and motorcycle_sales), the first step is to install the ODBC drivers required to create an ODBC DSN that can access Snowflake data. There are many, but the CDATA Snowflake ODBC Driver<\/a> is one that is easy to install and configure and allows you to connect with a live Snowflake data warehouse, directly from any application (that supports ODBC connectivity). Using these drivers, you can access Snowflake like you would any other database to read, write, and update through a standard ODBC Driver interface.<\/p>\n

    Once you\u2019ve downloaded and installed the CDATA drivers (I\u2019ve used version 22.0), you must create the actual DSN on the machine where the application (in this case IBM Planning Analytics) resides. Microsoft offers details on creating and configuring ODBC DSN\u2019s here<\/a> but here is a quick overview:<\/p>\n

    On the machine where Planning Analytics is running, open the ODBC Data Source Administrator<\/strong> and click on the System DSN<\/strong> tab. Click on Add, <\/strong>select \u201cCData ODBC Driver for Snowflake\u201d<\/strong> then click Finish<\/strong>.<\/p>\n

    \"\"<\/p>\n

    At this point the \u201cCData ODBC Driver for Snowflake \u2013 DSN Configuration\u201d<\/strong> dialog will appear where you can enter the required parameters:<\/p>\n