Visualize Greenplum Data in Tableau

The CData ODBC Driver for Greenplum enables you to access live Greenplum data in business intelligence tools like Tableau. In this article, you will integrate Greenplum data into a dashboard that reflects changes to Greenplum data in real time.

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

Connect to Greenplum 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.

To connect to Greenplum, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. If the Database property is not specified, the default database for the authenticate user is used.

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.

Add Greenplum Data to a Dashboard

1. Click Connect to Data -> More Servers -> Other Databases (ODBC).
   Select the CData Data Source Name (for example: CData Greenplum Source).
2. In the Database menu, select CData.
3. In the Table box, enter a table name or click New Custom SQL to enter an SQL query. This article retrieves the Orders table.
4. Drag the table onto the join area. At this point, you can include multiple tables, leveraging the built-in SQL engine to process complex data requests. 👁 A connection to a single table. (Google Sheets is shown.)
   
5. In the Connection menu, select the Live option, so that you skip loading a copy of the data into Tableau and instead work on real-time data. The optimized data processing native to CData ODBC drivers enables unmatched performance in live connectivity.
6. Click the tab for your worksheet. Columns are listed as Dimensions and Measures, depending on the data type. The CData driver discovers data types automatically, allowing you to leverage the powerful data processing and visualization features of Tableau.
7. Drop the Freight column in the Dimensions pane onto the dashboard. When you select dimensions, Tableau builds a query to the driver. The results are grouped based on that dimension. In Tableau, the raw query is automatically modified as you select dimensions and measures.

8. Drag the ShipName column in the Measures field onto the Detail and Color buttons. Tableau executes the following query:

   SELECT Freight, SUM(ShipName) FROM Orders GROUP BY Freight
   

   When you select a measure, Tableau executes a command to the driver to calculate a summary function, such as SUM, AVG, etc., on the grouped values. The SQL engine (embedded within the driver) is leveraged to process the aggregation of the data, where needed, providing a seamless experience in Tableau, regardless of the data source.

   To change the summary function, open the ShipName menu and select the summary you want in the Measure command.

   👁 A simple visualization that shows the latest data.
   

9. You can create other charts using dimensions and measures to build SQL queries visually:

   👁 A dashboard with several visualizations. The SQL query that corresponds to each chart is shown next to the chart. (Google Sheets is shown.)
   

With the CData ODBC Driver for Greenplum, you get live connectivity to your Greenplum data, allowing you to build real-time charts, graphs, and more.