SAP Analytics Cloud is a cloud-based business intelligence platform. CData Connect AI creates a pure, cloud-to-cloud connection to SQL Server and can be used to generate an OData API (natively supported in Analytics Cloud) for SQL Server. By pairing SAP Analytics Cloud with CData Connect AI, you get true cloud-to-cloud connectivity to all of your SaaS and cloud-based Big Data and NoSQL sources — no need to migrate your data or write your integrations. Simply connect to Connect AI as you would any other OData service and get instant, consolidated access to all of your data.
In this article, we walk through connecting to SQL Server from SAP Analytics Cloud (through CData Connect AI) to create a model and build a simple dashboard.
Connect to SQL Server from SAP Analytics Cloud
To work with live SQL Server data in SAP Analytics Cloud, we need to connect to SQL Server from Connect AI, provide user access to
the connection, and create a Workspace for the SQL Server data.
Connect to SQL Server from Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
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Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection
- Select "SQL Server" from the Add Connection panel
👁 Selecting a data source
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Enter the necessary authentication properties to connect to SQL Server.
Connecting to Microsoft SQL Server
Connect to Microsoft SQL Server using the following properties:
- Server: The name of the server running SQL Server.
- User: The username provided for authentication with SQL Server.
- Password: The password associated with the authenticating user.
- Database: The name of the SQL Server database.
Connecting to Azure SQL Server and Azure Data Warehouse
You can authenticate to Azure SQL Server or Azure Data Warehouse by setting the following connection properties:
- Server: The server running Azure. You can find this by logging into the Azure portal and navigating to "SQL databases" (or "SQL data warehouses") -> "Select your database" -> "Overview" -> "Server name."
- User: The name of the user authenticating to Azure.
- Password: The password associated with the authenticating user.
- Database: The name of the database, as seen in the Azure portal on the SQL databases (or SQL warehouses) page.
SSH Connectivity for SQL Server
You can use SSH (Secure Shell) to authenticate with SQL Server, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).
SSH Connections to SQL Server in Password Auth Mode
To connect to SQL Server via SSH in Password Auth mode, set the following connection properties:
- User: SQL Server User name
- Password: SQL Server Password
- Database: SQL Server database name
- Server: SQL Server Server name
- Port: SQL Server port number like 3306
- UserSSH: "true"
- SSHAuthMode: "Password"
- SSHPort: SSH Port number
- SSHServer: SSH Server name
- SSHUser: SSH User name
- SSHPassword: SSH Password
SSH Connections to SQL Server in Public Key Auth Mode
To connect to SQL Server via SSH in Password Auth mode, set the following connection properties:
- User: SQL Server User name
- Password: SQL Server Password
- Database: SQL Server database name
- Server: SQL Server Server name
- Port: SQL Server port number like 3306
- UserSSH: "true"
- SSHAuthMode: "Public_Key"
- SSHPort: SSH Port number
- SSHServer: SSH Server name
- SSHUser: SSH User name
- SSHClientCret: the path for the public key certificate file
👁 Configuring a connection (Salesforce is shown)
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Click Save & Test
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Navigate to the Permissions tab in the Add SQL Server 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.
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Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
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On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
👁 Creating a new PAT
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The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
Configure SQL Server Endpoints for SAP Analytics Cloud
After connecting to SQL Server, create a workspace for your desired table(s).
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Navigate to the Workspaces page and click Add to create a new Workspace (or select an existing workspace).
👁 The Workspaces page.
👁 Adding a new Workspace.
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Click Add to add new assets to the Workspace.
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Select the SQL Server connection (e.g. SQL1) and click Next.
👁 Selecting an Asset (Salesforce is shown).
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Select the table(s) you wish to work with and click Confirm.
👁 Selecting Tables (Salesforce is shown).
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Make note of the OData Service URL for your workspace, e.g. https://cloud.cdata.com/api/odata/{workspace_name}
With the connection, PAT, and Workspace configured, you are ready to connect to SQL Server data from SAP Analytics Cloud.
Create a Model of SQL Server Data in SAP Analytics Cloud
With the connection to SQL Server configured and the OData endpoint(s) created, we can create a Model for SQL Server data in SAP Analytics Cloud.
- Log into your Analytics Cloud instance and click Create -> Model from the menu.
- Choose "Get data from a datasource" and select "OData Services"
- Choose an existing connection to your Connect AI OData or Create a new one:
- Set Connection Name
- Set Data Service URL to the Base URL for your OData API: https://cloud.cdata.com/api/odata/{workspace_name}
- Set Authentication Type to Basic Authentication
- Set User Name to the Connect AI user (e.g. [email protected])
- Set Password to the PAT for the above user
👁 Creating a new OData Services Connection
- Choose "Create a new query" and click Next
- Name the Execute, select an OData endpoint (like Orders) and click Next
👁 Choosing a Connect AI OData endpoint to query
- Drag the columns you wish to work with into the Selected Data workspace and click Create
👁 Selecting fields (columns) from the OData endpoint
- At this point, a Draft Data source is created; click the draft to finalize the model
- Perform any transformations, including creating calculated dimensions, location dimensions, and combining data sources, then click Create Model
👁 Finalizing the model
- Name your model and click OK
Build a Dashboard in SAP Analytics Cloud
With the model created, you are ready to create a dashboard in SAP Analytics Cloud based on SQL Server data.
- From the menu, click Create -> Story
- Click on SAP Analytics Template (this article uses the "Dashboard" template)
- Choose a layout and click Apply
- From the More menu, select a visualization to insert (Chart)
👁 Inserting a visualization
- Select a model to visualize
- Select a structure and the required Measures and Dimensions
- Save the store
👁 Saving the Story
More Information & Free Trial
Now, you have created a simple but powerful dashboard from live SQL Server data. For more information on creating OData feeds from SQL Server (and more than 100 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live SQL Server data in SAP Analytics Cloud.
