Analyze SQL Analysis Services Data in Looker

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use CData Connect AI to connect to SQL Analysis Services Data from Looker and build custom apps using live SQL Analysis Services data.

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 SQL Analysis Services data for business applications. This article shows how to connect to SQL Analysis Services in Connect AI and then connect to SQL Analysis Services data in Looker.

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

Configure SQL Analysis Services Connectivity for Looker

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "SQL Analysis Services" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to SQL Analysis Services.

    To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

    To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

    • HTTP Authentication

      Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

    • Windows (NTLM)

      Set the Windows User and Password and set AuthScheme to "NTLM".

    • Kerberos and Kerberos Delegation

      To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

    • SSL/TLS:

      By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

    You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

    See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add SQL Analysis Services 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 SQL Analysis Services data from Looker.

Connect to SQL Analysis Services in Looker

The steps below outline connecting to CData Connect AI from Looker to create a new SQL Analysis Services 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 SQL Analysis Services 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!

Ready to get started?

Learn more about CData Connect AI or sign up for free trial access:

Free Trial