Connect to Live Azure Data Lake Storage Data in MicroStrategy through CData Connect Server

MicroStrategy is an analytics and mobility platform that enables data-driven innovation. When you pair MicroStrategy with CData Connect Server, you gain database-like access to live Azure Data Lake Storage data from MicroStrategy, expanding your reporting and analytics capabilities. In this article, we walk through creating a virtual database for Azure Data Lake Storage in Connect Server and connecting to Connect Server in MicroStrategy to create a simple visualization of Azure Data Lake Storage data.

As a hosted integration platform, Connect Server is ideal for working with cloud-based BI and analytics tools. With no servers to configure or data proxies to set up, you can simply use the web-based UI to create a virtual database for Azure Data Lake Storage and connect from MicroStrategy to start performing analytics based on live Azure Data Lake Storage data.

Connect to Azure Data Lake Storage from MicroStrategy

To work with live Azure Data Lake Storage data in MicroStrategy, we need to create a virtual database for Azure Data Lake Storage in Connect Server.

Create a Virtual SQL Server Database for Azure Data Lake Storage Data

CData Connect Server uses a straightforward, point-and-click interface to connect to data sources and generate APIs.

1. Login to Connect Server and click Connections.
2. Select "Azure Data Lake Storage" from Available Data Sources.
3. 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:

   1. Sign in to your Azure Account through the .
   2. Select "Azure Active Directory".
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   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.
4. Click Save Changes
5. Click Privileges -> Add and add the new user (or an existing user) with the appropriate permissions.

With the virtual database created, you are ready to connect to Azure Data Lake Storage data from MicroStrategy.

Connect to and Visualize Azure Data Lake Storage Data Using MicroStrategy

You can connect to Azure Data Lake Storage in MicroStrategy by adding a data source based on the native SQL Server functionality. Once you have created a data source, you can build dynamic visualizations of Azure Data Lake Storage data in MicroStrategy.

1. Open MicroStrategy and select your account.
2. Click Add External Data, select Databases, and use Select Tables as the Import Option.
3. In the Import from Tables wizard, click to add a new Data Source.
4. Select "SQL Server" in the Database menu and select "SQL Server 2017" in the Version menu.
5. Sat the connection properties as follows:
   • Server Name: e.g. connect_server_url
   • Port Number: 1433
   • Database Name: the name of your Azure Data Lake Storage connection (e.g. ADLS1)
   • User: a Connect Server user
   • Password: a Connect Server password
   • Data Source Name: a name for the new external data source, like "CData Connect Azure Data Lake Storage"
6. Expand the menu for the new data source and choose "Edit Catalog Options"
7. Edit the "SQL statement retrieve columns ..." query to include TABLE_SCHEMA = '#?Schema_Name?#' in the WHERE clause, and click Apply and then OK (the complete query is below).
   
   

   SELECT DISTINCT 
     TABLE_SCHEMA NAME_SPACE, 
     TABLE_NAME TAB_NAME, 
     COLUMN_NAME COL_NAME, 
     (CASE 
       WHEN 
         (DATA_TYPE LIKE '%char' AND (CHARACTER_SET_NAME='utf8' OR CHARACTER_SET_NAME='usc2')) 
       THEN 
         CONCAT('a',DATA_TYPE) 
       ELSE 
         DATA_TYPE 
     END) DATA_TYPE, 
     CHARACTER_MAXIMUM_LENGTH DATA_LEN, 
     NUMERIC_PRECISION DATA_PREC, 
     NUMERIC_SCALE DATA_SCALE 
   FROM 
     INFORMATION_SCHEMA.COLUMNS 
   WHERE 
     TABLE_NAME 
   IN 
     (#TABLE_LIST#) AND TABLE_SCHEMA='#?Schema_Name?#' 
   ORDER BY 
     1,2,3
   

8. Select the new data source and select the Namespace that corresponds to your virtual Azure Data Lake Storage database (like ADLS1).
9. Drag tables into the pane to insert then. Note: Since we create a live connection, we can insert whole tables and utilize the filtering and aggregation features native to the MicroStrategy products to customize our datasets.
10. Click Finish, choose the option to connect live, save the query, and choose the option to create a new dossier. Live connections are possible and effective, thanks to high-performance data processing native to CData Connect Cloud.
11. Choose a visualization, choose fields to display, and apply any filters to create a new visualization of Azure Data Lake Storage data. Data types are discovered automatically through dynamic metadata discovery. Where possible, the complex queries generated by the filters and aggregations will be pushed down to Azure Data Lake Storage, while any unsupported operations (which can include SQL functions and JOIN operations) will be managed by the CData SQL engine embedded in Connect Cloud.
12. Once you have finished configuring the dossier, click File -> Save.

Using CData Connect Server with MicroStrategy, you can easily create robust visualizations and reports on Azure Data Lake Storage data. For more information on creating virtual databases for 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 MicroStrategy.