Build Asana-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Asana enables users to access live Asana data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Asana data to any data source natively supported in Google Data Fusion, this article explains how to pipe data from Asana to Google BigQuery,

Upload the CData JDBC Driver for Asana to Google Data Fusion

Upload the CData JDBC Driver for Asana to your Google Data Fusion instance to work with live Asana data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdataasana-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver 👁 Image
   
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.asana) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.asana.AsanaDriver)
   👁 Configuring the driver (Salesforce is shown.)
   
5. Click "Finish"

Connect to Asana Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Asana data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver 👁 Adding a database source
   
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-asana)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Asana. For example:
     
     jdbc:asana:RTK=5246...;OAuthClientId=YourClientId;OAuthClientSecret=YourClientSecret;CallbackURL='http://localhost:33333';InitiateOAuth=GETANDREFRESH;

     You can optionally set the following to refine the data returned from Asana.

     • WorkspaceId: Set this to the globally unique identifier (gid) associated with your Asana Workspace to only return projects from the specified workspace. To get your workspace id, navigate to https://app.asana.com/api/1.0/workspaces while logged into Asana. This displays a JSON object containing your workspace name and Id.
     • ProjectId: Set this to the globally unique identifier (gid) associated with your Asana Project to only return data mapped under the specified project. Project IDs can be found in the URL of your project's Overview page. This will be the numbers directly after /0/.

     Connect Using OAuth Authentication

     You must use OAuth to authenticate with Asana. OAuth requires the authenticating user to interact with Asana using the browser. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the Asana JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.asana.jar
      

     Fill in the connection properties and copy the connection string to the clipboard.

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
   • Set Import Query to a SQL query that will extract the data you want from Asana, i.e.:
     SELECT * FROM projects
   👁 Configuring the database source
   
4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
5. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like asana-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert Asana data into
   👁 Configuring the BigQuery sink
   

With the Source and Sink configured, you are ready to pipe Asana data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Asana and import it into Google BigQuery. 👁 Image

While this is a simple pipeline, you can create more complex Asana pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Asana and start working with your live Asana data in Google Data Fusion today.