Create Data Visualizations Based On SQL Analysis Services Data in Mode

Mode is a collaborative data platform that combines SQL, R, Python, and visual analytics in one place. When paired with CData Connect AI, you get instant, cloud-to-cloud access to SQL Analysis Services data for use in data visualizations. This article shows how to connect to SQL Analysis Services in Connect AI, connect to SQL Analysis Services data in Mode, and create a simple visualization using that data.

CData Connect AI provides a pure cloud-to-cloud interface for SQL Analysis Services, allowing you to build data visualizations from live SQL Analysis Services data in Mode — without replicating the data to a natively supported database. In order to create visualizations, users write 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 Mode

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

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

2. Select "SQL Analysis Services" from the Add Connection panel

3. 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.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add SQL Analysis Services 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 SQL Analysis Services data from Mode.

Connect to SQL Analysis Services in Mode

The steps below outline connecting to CData Connect AI from Mode to create a new SQL Analysis Services data source.

1. Log-in to Mode
2. In the top-left corner of the screen, click the down-arrow next to your name and select Connect a Database...
3. On the next screen, select Microsoft SQL Server.
4. Enter the Microsoft SQL Server credentials:
   • Display Name: the name for the connection.
   • Host/Port: enter tds.cdata.com in the Host field and 14333 in the Port field.
   • Database name: enter the Connection Name of the CData Connect AI data source you want to connect to (for example, SSAS1).
   • 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.
5. At the bottom of the page, click Connect to ensure that you can connect to CData Connect AI.
6. Upon success, the following screen appears.

Your connection is now available for use in Mode. 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 Mode Visualization

To create a visualization in Mode, follow these steps:

1. On the current screen, click New Report. The SQL query text editor appears. Enter the following query:

   			SELECT * FROM [SSAS].[Adventure_Works];
   		

   Click Run. The app now shows the query result:
2. Running the query activates the New Chart tab. Click this tab and select Pie Chart.
3. Now, drop a dimension in the Color section and a measure in the Angle section.

   We have now created a visualization of SQL Analysis Services data in Mode using CData Connect AI!

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