Connect to and Visualize Live REST Data in Tableau Prep

Tableau is a visual analytics platform transforming the way businesses use data to solve problems. When paired with the CData Tableau Connector for REST, you can easily get access to live REST data within Tableau Prep. This article shows how to connect to REST in Tableau Prep and build a simple chart.

The CData Tableau Connectors enable high-speed access to live REST data in Tableau. Once you install the connector, you simply authenticate with REST and you can immediately start building responsive, dynamic visualizations and dashboards. By surfacing REST data using native Tableau data types and handling complex filters, aggregations, & other operations automatically, CData Tableau Connectors grant seamless access to REST data.

NOTE: The CData Tableau Connectors support Tableau Prep Builder 2020.4.1 or higher. If you are using an older version of Tableau Prep Builder, you will need to use the CData JDBC Driver.

Install the CData Tableau Connector

When you install the CData Tableau Connector for REST, the installer should copy the TACO and JAR files to the appropriate directories. If your data source does not appear in the connection steps below, you will need to copy two files:

1. Copy the TACO file (cdata.rest.taco) found in the lib folder of the connector's installation location (C:\Program Files\CData\CData Tableau Connector for REST 20XX\lib on Windows) to the Tableau Prep Builder repository:
   • Windows: C:\Users\[Windows User]\Documents\My Tableau Prep Repository\Connectors
   • MacOS: /Users//Documents/My Tableau Prep Repository/Connectors
2. Copy the JAR file (cdata.tableau.rest.jar) found in the same lib folder to the Tableau drivers directory, typically [Tableau installation location]\Drivers.

Connect to REST in Tableau Prep Builder

Open Tableau Prep Builder and click "Connect to Data" and search for "REST by CData." Configure the connection and click "Sign In."

See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models REST APIs as bidirectional database tables and XML/JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

After setting the and providing any authentication values, set to "XML" or "JSON" and set to more closely match the data representation to the structure of your data.

The property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

• Document (default): Model a top-level, document view of your REST data. The data provider returns nested elements as aggregates of data.
• FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
• Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

See the Modeling REST Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

👁 Configuring the Connector (Sage Intacct is shown)

Discover and Prep Data

Drag the tables and views you wish to work with onto the canvas. You can include multiple tables.

👁 Selecting table(s)

Data Cleansing & Filtering

To further prepare the data, you can implement filters, remove duplicates, modify columns and more.

1. Start by clicking on the plus next to your table and selecting the Clean Step option. 👁 Adding a Clean Step
   
2. Select the field values to filter by. As you select values, you can see how your selections impact other fields. 👁 Selecting test entries (Sage Intacct is shown).
   
3. Opt to "Keep Only" or "Exclude" entries with your select values and the data changes in response. 👁 Excluding selected entries (Sage Intacct is shown).
   

Data Joins and Unions

Data joining involves combining data from two or more related tables based on a common field or key.

1. To join multiple tables, drag a related table next to an existing table in the canvas and place it in the Join box. 👁 Joining two tables (Sage Intacct is shown).
   
2. Select the foreign keys that exist in both tables. 👁 Setting the joining fields/columns (Sage Intacct is shown).
   

Exporting Prepped Data

After you perform any cleansing, filtering, transformations, and joins, you can export the data for visualization in Tableau.

1. Add any other needed transformations then insert an Output node at the end of the flow.
2. Configure the node to save to a file in the format of your choice. 👁 Saving the results (Sage Intacct is shown).
   

Once the output data is saved, you can work with it in Tableau, just like you would any other file source.

Using the CData Tableau Connector for REST with Tableau Prep Builder, you can easily join, cleanse, filter, and aggregate REST data for visualizations and reports in Tableau. Download a free, 30-day trial and get started today.