Analyze Azure Table Data in Looker

Looker is a business intelligence and big data analytics platform that helps you explore, analyze and share real-time business analytics. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Azure Table data for business applications. This article shows how to connect to Azure Table in Connect AI and then connect to Azure Table data in Looker.

CData Connect AI provides a pure cloud-to-cloud interface for Azure Table, allowing you to build reports from live Azure Table data in Looker — without replicating the data to a natively supported database. As you create applications to work with data, Looker generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc.) directly to Azure Table, leveraging server-side processing to quickly return the requested Azure Table data.

Configure Azure Table Connectivity for Looker

Connectivity to Azure Table from Looker is made possible through CData Connect AI. To work with Azure Table data from Looker, we start by creating and configuring a Azure Table connection.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Azure Table" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Azure Table.

   Specify your AccessKey and your Account to connect. Set the Account property to the Storage Account Name and set AccessKey to one of the Access Keys. Either the Primary or Secondary Access Keys can be used. To obtain these values, navigate to the Storage Accounts blade in the Azure portal. You can obtain the access key by selecting your account and clicking Access Keys in the Settings section.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Azure Table Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Azure Table data from Looker.

Connect to Azure Table in Looker

The steps below outline connecting to CData Connect AI from Looker to create a new Azure Table data source.

1. Log-in to Looker
2. In the navigation pane, select Admin. 👁 Selecting Admin
   
3. Under the Database category, select Connections. 👁 Selecting connections
   
4. On the Connections page, click Add Connection. 👁 Adding a new connection
   
5. Enter the connection settings:
   • Name: the name for the connection in models.
   • Dialect: select Microsoft SQL Server 2017+.
   • SSH Server: leave this disabled.
   • Remote Host:Port: enter tds.cdata.com in the first field and 14333 in the second field.
   • Database: enter the Connection Name of the CData Connect AI data source you want to connect to (for example, QuickBooksOnline1).
   • Username: enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected]
   • Password: enter the PAT you generated on the Settings page
   Leave the rest of the connection settings at their default values unless you need to modify them. 👁 Configuring connection settings
   
6. At the bottom of the page, click Test These Settings to ensure that you can connect to CData Connect AI.
7. Click Add Connection to create the connection and return to the Connections page. 👁 New connection added.
   

Your connection is now available for use in Looker. To connect to additional data sources from your CData Connect AI account, repeat the setup steps above, changing the value for Database for each data source.

Creating A Looker Visualization From The SQL Runner and Explore Features

To create a visualization in Looker using the SQL Runner, follow these steps:

1. In the Looker interface, select Develop -> SQL Runner from the left navigation pane. 👁 Select SQL Runner.
   
2. On the SQL Runner interface, select the connection you made in the previous steps. 👁 Entering name for new dashboard.
   
3. Now, click the gear symbol next to a table and then select Explore Table. 👁 Entering name for new dashboard.
   
4. Next, on the left menu, select fields from the table and click Run. You can now expand the Visualization accordion, and see a bar chart, by default. 👁 Entering name for new dashboard.
   

   We have now created a visualization of Azure Table data in Looker using CData Connect AI!

Get CData Connect AI

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today!