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Get the Report →Build an OLAP Cube in SSAS from MongoDB Data
Establish a connection to MongoDB data data from SQL Server Analysis Services, and use the MongoDB Data Provider to build OLAP cubes for use in analytics and reporting.
SQL Server Analysis Services (SSAS) serves as an analytical data engine employed in decision support and business analytics, offering high-level semantic data models for business reports and client applications like Power BI, Excel, Reporting Services reports, and various data visualization tools. When coupled with the CData ADO.NET Provider for MongoDB, you gain the capability to generate cubes from MongoDB data, facilitating more profound and efficient data analysis.
In this article, we will guide you through the process of developing and deploying a multi-dimensional model of MongoDB data by creating an Analysis Services project in Visual Studio. To proceed, ensure that you have an accessible SSAS instance and have installed the ADO.NET Provider.
About MongoDB Data Integration
Accessing and integrating live data from MongoDB has never been easier with CData. Customers rely on CData connectivity to:
- Access data from MongoDB 2.6 and above, ensuring broad usability across various MongoDB versions.
- Easily manage unstructured data thanks to flexible NoSQL (learn more here: Leading-Edge Drivers for NoSQL Integration).
- Leverage feature advantages over other NoSQL drivers and realize functional benefits when working with MongoDB data (learn more here: A Feature Comparison of Drivers for NoSQL).
MongoDB's flexibility means that it can be used as a transactional, operational, or analytical database. That means CData customers use our solutions to integrate their business data with MongoDB or integrate their MongoDB data with their data warehouse (or both). Customers also leverage our live connectivity options to analyze and report on MongoDB directly from their preferred tools, like Power BI and Tableau.
For more details on MongoDB use case and how CData enhances your MongoDB experience, check out our blog post: The Top 10 Real-World MongoDB Use Cases You Should Know in 2024.
Getting Started
Creating a Data Source for MongoDB
Start by creating a new Analysis Service Multidimensional and Data Mining Project in Visual Studio. Next, create a Data Source for MongoDB data in the project.
- In the Solution Explorer, right-click Data Source and select New Data Source.
- Opt to create a data source based on an existing or new connection and click New.
- In the Connection Manager, select CData ADO.NET Provider for MongoDB, enter the necessary connection properties, and click Next.
Set the Server, Database, User, and Password connection properties to connect to MongoDB. To access MongoDB collections as tables you can use automatic schema discovery or write your own schema definitions. Schemas are defined in .rsd files, which have a simple format. You can also execute free-form queries that are not tied to the schema.
When you configure the connection, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.
- Set the impersonation method to Inherit and click Next.
- Name the data source (CData MongoDB Source) and click Finish.
Creating a Data Source View
After you create the data source, create the data source view.
- In the Solution Explorer, right-click Data Source Views and select New Data Source View.
- Select the data source you just created (CData MongoDB Source) and click Next.
- Choose a foreign key match pattern that matches your underlying data source and click Next.
- Select MongoDB tables to add to the view and click Next.
- Name the view and click Finish
Based on the foreign key match scheme, relationships in the underlying data will be automatically detected. You can view (and edit) these relationships by double clicking Data Source View.
Note that adding a secondary data source to the Data Source View is not supported. When working with multiple data sources, SSAS requires both sources to support remote queries via OpenRowset which is unavailable in the ADO.NET Provider.
Creating a Cube for MongoDB
The last step before you can process the project and deploy MongoDB data to SSAS is creating the cubes.
- In the Solution Explorer, right-click Cubes and select New Cube
- Select "Use existing tables" and click Next.
- Select the tables that will be used for measure group tables and click Next.
- Select the measures you want to include in the cube and click Next.
- Select the dimensions to be created, based on the available tables, and click Next.
- Review all of your selections and click Finish.
Process the Project
With the data source, data source view, and cube created, you are ready to deploy the cube to SSAS. To configure the target server and database, right-click the project and select properties. Navigate to deployment and configure the Server and Database properties in the Target section.
After configuring the target server and database, right-click the project and select Process. You may need to build and deploy the project as a part of this step. Once the project is built and deployed, click Run in the Process Database wizard.
Now you have an OLAP cube for MongoDB data in your SSAS instance, ready to be analyzed, reported, and viewed. Get started with a free, 30-day trial of the CData ADO.NET Provider for MongoDB.