Create SQL Analysis Services-Connected Dashboards in Grafana

Grafana is an open-source platform that allows users to analyze, monitor, and visualize telemetry from various data sources. When combined with CData Connect AI, you gain immediate access to SQL Analysis Services data for business dashboards. This article outlines the process of connecting to SQL Analysis Services using Connect AI and creating a basic dashboard from SQL Analysis Services data within Grafana.

CData Connect AI offers a pure SQL Server, cloud-to-cloud interface for SQL Analysis Services, enabling the creation of dashboards directly from live SQL Analysis Services data within Grafana, all without the need for data replication to a native database. As you build visualizations, Grafana generates SQL queries to gather data. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to SQL Analysis Services. This leverages server-side processing to swiftly deliver the requested SQL Analysis Services data.

Configure SQL Analysis Services Connectivity for Grafana

Connectivity to SQL Analysis Services from Grafana is made possible through CData Connect AI. To work with SQL Analysis Services data from Grafana, 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 Grafana.

Visualize Live SQL Analysis Services Data in Grafana

To establish a connection from Grafana to the CData Connect AI Virtual SQL Server API, follow these steps.

1. If you have not already done so, download and install Grafana for your operating system from the Grafana Website. Once installed, access Grafana at http://localhost:3000/.
2. Log in to Grafana with your username and password for Grafana. If this is your first time logging in, the username is admin and the password is admin.
3. On the navigation menu, click Sources > Add new connection. On this page, you can search for Microsoft SQL Server and select it as your data source.
4. Select Microsoft SQL Server and click Add new data source.
5. Enter a name for the new data source and then enter the following connection settings:
   • Host: tds.cdata.com:14333
   • Database: 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 previously generated.
   
6. Click Save & Test. A Database Connect OK message appears when you have a successful connection established.

Create a Dashboard

Once you create the data source for SQL Analysis Services, you can start building dashboards on SQL Analysis Services data. Start in the navigation menu and click Dashboards

1. On the Dashboards page, click + Create dashboard, then click + Add visualization.
2. This opens the Select data source window where you can select your created connection.
3. After selecting your connection, you can choose the tables and columns that you want to query for your visualization. Then press Run Query to run the generated query.
4. After running your query, the resulting data is populated above the query editor. Here you can select the visualization that you want to use to present your data on the dashboard panel.
5. When you have finished editing your panel, you can click Save dashboard to save the changes made to your Dashboard.

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