Build an OLAP Cube in SSAS from CSV Data

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 CSV, you gain the capability to generate cubes from CSV 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 CSV 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.

Creating a Data Source for CSV

Start by creating a new Analysis Service Multidimensional and Data Mining Project in Visual Studio. Next, create a Data Source for CSV data in the project.

1. In the Solution Explorer, right-click Data Source and select New Data Source.
2. Opt to create a data source based on an existing or new connection and click New.
3. In the Connection Manager, select CData ADO.NET Provider for CSV, enter the necessary connection properties, and click Next.

   Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files

   CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

   Setting connection properties for local files

   Set the URI property to local folder path.

   Setting connection properties for files stored in Amazon S3

   To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:

   • AWSAccessKey: AWS Access Key (username)
   • AWSSecretKey: AWS Secret Key

   Setting connection properties for files stored in Box

   To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.

   Dropbox

   To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

   SharePoint Online (SOAP)

   To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.

   SharePoint Online REST

   To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

   Google Drive

   To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

   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.

   👁 Setting the Connection properties (Salesforce is shown.)
   
4. Set the impersonation method to Inherit and click Next. 👁 Setting the impersonation method.
   
5. Name the data source (CData CSV Source) and click Finish.

Creating a Data Source View

After you create the data source, create the data source view.

1. In the Solution Explorer, right-click Data Source Views and select New Data Source View.
2. Select the data source you just created (CData CSV Source) and click Next.
3. Choose a foreign key match pattern that matches your underlying data source and click Next. 👁 Selecting the Foreign key match pattern.
   
4. Select CSV tables to add to the view and click Next. 👁 Selecting Tables (Salesforce is shown).
   
5. 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 CSV

The last step before you can process the project and deploy CSV data to SSAS is creating the cubes.

1. In the Solution Explorer, right-click Cubes and select New Cube
2. Select "Use existing tables" and click Next.
3. Select the tables that will be used for measure group tables and click Next. 👁 Selecting measure group tables (Salesforce is shown).
   
4. Select the measures you want to include in the cube and click Next. 👁 Selecting measures (Salesforce is shown).
   
5. Select the dimensions to be created, based on the available tables, and click Next. 👁 Selecting dimensions (Salesforce is shown).
   
6. 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 CSV 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 CSV.