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Connect to and Query YouTube Analytics Data in QlikView over ODBC

Create data visualizations with YouTube Analytics data in QlikView.

The CData ODBC drivers expand your ability to work with data from more than 200 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 YouTube Analytics data using the CData ODBC driver and create data visualizations in QlikView.

The CData ODBC drivers offer unmatched performance for interacting with live YouTube Analytics data in QlikView due to optimized data processing built into the driver. When you issue complex SQL queries from QlikView to YouTube Analytics, the driver pushes supported SQL operations, like filters and aggregations, directly to YouTube Analytics 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 YouTube Analytics data using native QlikView data types.

Connect to YouTube Analytics 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.

YouTube Analytics uses the OAuth authentication standard. You can use the embedded CData OAuth credentials or you can register an application with Google to obtain your own.

In addition to the OAuth values, to access YouTube Analytics data set ChannelId to the Id of a YouTube channel. You can obtain the channel Id in the advanced account settings for your channel. If not specified, the channel of the currently authenticated user will be used.

If you want to generate content owner reports, specify the ContentOwnerId property. This is the Id of the copyright holder for content in YouTube's rights management system. The content owner is the person or organization that claims videos and sets their monetization policy.

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 YouTube Analytics 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 Snippet_Title, ContentDetails_ItemCount FROM Groups
  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.
  3. Select the DSN (CData YouTubeAnalytics Sys) in the resulting dialog. A command like the following is generated: ODBC CONNECT TO [CData YouTubeAnalytics 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 Snippet_Title, ContentDetails_ItemCount FROM Groups;

    Where possible, the SQL operations in the query, like filters and aggregations, will be pushed down to YouTube Analytics, 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.

  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 YouTube Analytics, typed appropriately for QlikView, thanks to built-in dynamic metadata querying.
  7. When defining Dimensions, select Snippet_Title in the First Dimension menu.
  8. When defining Expressions, click the summary function you want and select ContentDetails_ItemCount in the menu.
  9. Finish the wizard to generate the chart. The CData ODBC Driver for YouTube Analytics connects to live YouTube Analytics 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.