Analyze JSON Services 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 JSON services for business applications. This article shows how to connect to JSON in Connect AI and then connect to JSON services in Looker.

CData Connect AI provides a pure cloud-to-cloud interface for JSON, allowing you to build reports from live JSON services 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 JSON, leveraging server-side processing to quickly return the requested JSON services.

Configure JSON Connectivity for Looker

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

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

2. Select "JSON" from the Add Connection panel

3. Enter the necessary authentication properties to connect to JSON.

   See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models JSON APIs as bidirectional database tables and 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 URI and providing any authentication values, set DataModel to more closely match the data representation to the structure of your data.

   The DataModel 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 JSON 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 JSON 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.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add JSON Connection page and update the User-based 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.
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 JSON services from Looker.

Connect to JSON in Looker

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

1. Log-in to Looker
2. In the navigation pane, select Admin.
3. Under the Database category, select Connections.
4. On the Connections page, click Add 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.
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.

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.
2. On the SQL Runner interface, select the connection you made in the previous steps.
3. Now, click the gear symbol next to a table and then select Explore Table.
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.

   We have now created a visualization of JSON services 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!