Connect to and Query Azure Data Catalog Data in QlikView over ODBC

The CData ODBC drivers expand your ability to work with data from hundreds of data sources. QlikView is a business discovery platform that provides self-service BI for all business users in an organization. This article outlines simple steps to connect to Azure Data Catalog data using the CData ODBC driver and create data visualizations in QlikView.

The CData ODBC drivers offer unmatched performance for interacting with live Azure Data Catalog data in QlikView due to optimized data processing built into the driver. When you issue complex SQL queries from QlikView to Azure Data Catalog, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Data Catalog and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze Azure Data Catalog data using native QlikView data types.

Connect to Azure Data Catalog as an ODBC Data Source

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

You can optionally set the following to read the different catalog data returned from Azure Data Catalog.

<>CatalogName: Set this to the CatalogName associated with your Azure Data Catalog. To get your Catalog name, navigate to your Azure Portal home page > Data Catalog > Catalog Name

Connect Using OAuth Authentication

You must use OAuth to authenticate with Azure Data Catalog. OAuth requires the authenticating user to interact with Azure Data Catalog using the browser. For more information, refer to the OAuth section in the help documentation.

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Populate a Chart with Azure Data Catalog Data

The steps below supply the results of an SQL query to a visualization in QlikView. In this article, you will create a bar chart with the query below:

SELECT DslAddressDatabase, Type FROM Tables WHERE Name = 'FactProductInventory'

1. Click File -> Edit Script (or click the Edit Script button in the Toolbar).
2. On the Data tab, select ODBC in the Database menu and click Connect. 👁 Connecting to an ODBC data source.
   
3. Select the DSN (CData AzureDataCatalog Sys) in the resulting dialog. 👁 Selecting a DSN (Salesforce is shown).
   A command like the following is generated:

   ODBC CONNECT TO [CData AzureDataCatalog Sys];
   

4. Enter the SQL query directly into the script with the SQL command (or click Select to build the query in the SELECT statement wizard).

   SQL SELECT DslAddressDatabase, Type FROM Tables WHERE Name = 'FactProductInventory';
   

   Where possible, the SQL operations in the query, like filters and aggregations, will be pushed down to Azure Data Catalog, while any unsupported operations (which can include SQL functions and JOIN operations) will be managed client-side by the CData SQL engine embedded in the driver.

   👁 A script that connects and executes an SQL query. (Salesforce is shown.)
   
5. Close the script editor and reload the document to execute the script.
6. Click Tools -> Quick Chart Wizard. In the wizard, select the chart type. This example uses a bar chart. When building the chart, you have access to the fields from Azure Data Catalog, typed appropriately for QlikView, thanks to built-in dynamic metadata querying.
7. When defining Dimensions, select DslAddressDatabase in the First Dimension menu.
8. When defining Expressions, click the summary function you want and select Type in the menu.

9. Finish the wizard to generate the chart. The CData ODBC Driver for Azure Data Catalog connects to live Azure Data Catalog data, so the chart can be refreshed to see real-time changes. Live connections are possible and effective, thanks to the high-performance data processing native to CData ODBC Drivers.

   👁 A chart populated with the results of a query. (Salesforce is shown.)