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Connect to and Query Gmail Data in QlikView over ODBC

Create data visualizations with Gmail 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 Gmail data using the CData ODBC driver and create data visualizations in QlikView.

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

Connect to Gmail 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.

There are two ways to authenticate to Gmail. Before selecting one, first ensure that you have enabled IMAP access in your Gmail account settings. See the "Connecting to Gmail" section under "Getting Started" in the installed documentation for a guide.

The User and Password properties, under the Authentication section, can be set to valid Gmail user credentials.

Alternatively, instead of providing the Password, you can use the OAuth authentication standard. To access Google APIs on behalf on individual users, you can use the embedded credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

In addition to the OAuth values, you will need to provide the User. See the "Getting Started" chapter in the help documentation for a guide to using OAuth.

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 Gmail 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 Subject, Size FROM Inbox
  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 Gmail Sys) in the resulting dialog. A command like the following is generated: ODBC CONNECT TO [CData Gmail 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 Subject, Size FROM Inbox;

    Where possible, the SQL operations in the query, like filters and aggregations, will be pushed down to Gmail, 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 Gmail, typed appropriately for QlikView, thanks to built-in dynamic metadata querying.
  7. When defining Dimensions, select Subject in the First Dimension menu.
  8. When defining Expressions, click the summary function you want and select Size in the menu.
  9. Finish the wizard to generate the chart. The CData ODBC Driver for Gmail connects to live Gmail 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.