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Get the Report →Analyze Azure Data Lake Storage Data in SAP Analytics Cloud
Use the CData Connect Server to create an OData API on top of Azure Data Lake Storage data and visualize Azure Data Lake Storage data in SAP Analytics Cloud.
SAP Analytics Cloud is a cloud-based business intelligence platform. The CData Connect Server creates a virtual database for Azure Data Lake Storage and can be used to generate an OData API (natively consumable in Analytics Cloud) for Azure Data Lake Storage. By pairing SAP Analytics Cloud with the CData Connect Server, you get direct 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 Server 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 Azure Data Lake Storage in Connect Server and connecting to Connect Server from Analytics Cloud to create a model and build a simple dashboard.
Configure Connect Server to Connect to Azure Data Lake Storage
To connect to Azure Data Lake Storage data from SAP Analytics Cloud, you need to configure Azure Data Lake Storage access from your Connect Server instance. This means creating a user, connecting to Azure Data Lake Storage, adding OData endpoints, and (optionally) configuring CORS.
Add a Connect Server User
Create a User to connect to Azure Data Lake Storage from Analytics Cloud through Connect Server.
- Click Users -> Add
- Configure a User
- Click Save Changes and make note of the Authtoken for the new user
Connect to Azure Data Lake Storage from Connect Server
CData Connect Server uses a straightforward, point-and-click interface to connect to data sources and generate APIs.
- Open Connect Server and click Connections
- Select "Azure Data Lake Storage" from Available Data Sources
- Enter the necessary authentication properties to connect to Azure Data Lake Storage.
Authenticating to a Gen 1 DataLakeStore Account
Gen 1 uses OAuth 2.0 in Azure AD for authentication.
For this, an Active Directory web application is required. You can create one as follows:
To authenticate against a Gen 1 DataLakeStore account, the following properties are required:
- Schema: Set this to ADLSGen1.
- Account: Set this to the name of the account.
- OAuthClientId: Set this to the application Id of the app you created.
- OAuthClientSecret: Set this to the key generated for the app you created.
- TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
- Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
Authenticating to a Gen 2 DataLakeStore Account
To authenticate against a Gen 2 DataLakeStore account, the following properties are required:
- Schema: Set this to ADLSGen2.
- Account: Set this to the name of the account.
- FileSystem: Set this to the file system which will be used for this account.
- AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
- Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
- Click Save Changes
- Click Privileges -> Add, and add the new user (or an existing user) with the appropriate permissions (SELECT is all that is required for Reveal)
Add Azure Data Lake Storage OData Endpoints in Connect Server
After connecting to Azure Data Lake Storage, create OData Endpoint for the desired table(s).
- Click OData -> Tables -> Add Tables
- Select the Azure Data Lake Storage database
- Select the table(s) you wish to work with and click Next
- (Optional) Edit the resource to select specific fields and more
- Save the settings
(Optional) Configure Cross-Origin Resource Sharing (CORS)
When accessing and connecting to multiple different domains from an application such as Ajax, there is a possibility of violating the limitations of cross-site scripting. In that case, configure the CORS settings in OData -> Settings.
- Enable cross-origin resource sharing (CORS): ON
- Allow all domains without '*': ON
- Access-Control-Allow-Methods: GET, PUT, POST, OPTIONS
- Access-Control-Allow-Headers: Authorization
Save the changes to the settings.
Create a Model of Azure Data Lake Storage Data in SAP Analytics Cloud
With the connection to Azure Data Lake Storage configured and the OData endpoint(s) created, we can create a Model for Azure Data Lake Storage 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 Server OData or Create a new one:
- Set "Connection Name"
- Set "Data Service URL" to the Base URL for your OData API (typically: CONNECT_SERVER_URL/api.rsc)
- Set "Authentication Type" to Basic Authentication
- Set "User Name" to the Connect Server user you configured earlier
- Set "Password" to the Authtoken for the above user
- Choose "Create a new query" and click Next
- Name the Query, select an OData endpoint (like adlsdb_Resources) and click Next
- Drag the columns you wish to work with into the Selected Data workspace and click Create
- 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
- 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 Azure Data Lake Storage data.
- From the menu, click Create -> Story
- Click an 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)
- Select a model to visualize
- Select a structure and the required Measures and Dimensions
- Save the story
More Information & Free Trial
Now, you have created a simple but powerful dashboard from live Azure Data Lake Storage data. For more information on creating OData feeds from Azure Data Lake Storage (and more than 200 other data sources), visit the Connect Server page. Sign up for a free trial and start working with live Azure Data Lake Storage data in SAP Analytics Cloud.