Connect to and Visualize Live Harvest Data in Tableau Prep

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

The CData Tableau Connectors enable high-speed access to live Harvest data in Tableau. Once you install the connector, you simply authenticate with Harvest and you can immediately start building responsive, dynamic visualizations and dashboards. By surfacing Harvest data using native Tableau data types and handling complex filters, aggregations, & other operations automatically, CData Tableau Connectors grant seamless access to Harvest 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 API Driver for Tableau. If you wish to connect to Harvest data in Tableau Cloud, you will need to use CData Connect.

Install the CData Tableau Connector

When you install the CData Tableau Connector for Harvest, 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.api.taco) found in the lib folder of the connector's installation location (C:\Program Files\CData\CData Tableau Connector for Harvest 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.api.jar) found in the same lib folder to the Tableau drivers directory, typically [Tableau installation location]\Drivers.

Connect to Harvest in Tableau Prep Builder

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

Start by setting the Profile connection property to the location of the Harvest Profile on disk (e.g. C:\profiles\Harvest.apip). Next, set the ProfileSettings connection property to the connection string for Harvest (see below).

Harvest API Profile Settings

To authenticate to Harvest, you can use either Token authentication or the OAuth standard. Use Basic authentication to connect to your own data. Use OAuth to allow other users to connect to their data.

Using Token Authentication

To use Token Authentication, set the APIKey to your Harvest Personal Access Token in the ProfileSettings connection property. In addition to APIKey, set your AccountId in ProfileSettings to connect.

Using OAuth Authentication

First, register an OAuth2 application with Harvest. The application can be created from the "Developers" section of Harvest ID.

After setting the following connection properties, you are ready to connect:

• ProfileSettings: Set your AccountId in ProfileSettings.
• AuthScheme: Set this to OAuth.
• OAuthClientId: Set this to the client ID that you specified in your app settings.
• OAuthClientSecret: Set this to the client secret that you specified in your app settings.
• CallbackURL: Set this to the Redirect URI that you specified in your app settings.
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage how the driver obtains and refreshes the OAuthAccessToken.

Discover and Prep Data

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

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.
2. Select the field values to filter by. As you select values, you can see how your selections impact other fields.
3. Opt to "Keep Only" or "Exclude" entries with your select values and the data changes in response.

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.
2. Select the foreign keys that exist in both tables.

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.

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

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