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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 Amazon Athena, you gain the capability to generate cubes from Amazon Athena 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 Amazon Athena 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.
CData provides the easiest way to access and integrate live data from Amazon Athena. Customers use CData connectivity to:
Users frequently integrate Athena with analytics tools like Tableau, Power BI, and Excel for in-depth analytics from their preferred tools.
To learn more about unique Amazon Athena use cases with CData, check out our blog post: https://www.cdata.com/blog/amazon-athena-use-cases.
Start by creating a new Analysis Service Multidimensional and Data Mining Project in Visual Studio. Next, create a Data Source for Amazon Athena data in the project.
To authorize Amazon Athena requests, provide the credentials for an administrator account or for an IAM user with custom permissions: Set to the access key Id. Set to the secret access key.
Note: Though you can connect as the AWS account administrator, it is recommended to use IAM user credentials to access AWS services.
To obtain the credentials for an IAM user, follow the steps below:
To obtain the credentials for your AWS root account, follow the steps below:
If you are using the CData Data Provider for Amazon Athena 2018 from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. To do so, set to true and leave and empty. The CData Data Provider for Amazon Athena 2018 will automatically obtain your IAM Role credentials and authenticate with them.
In many situations it may be preferable to use an IAM role for authentication instead of the direct security credentials of an AWS root user. An AWS role may be used instead by specifying the . This will cause the CData Data Provider for Amazon Athena 2018 to attempt to retrieve credentials for the specified role. If you are connecting to AWS (instead of already being connected such as on an EC2 instance), you must additionally specify the and of an IAM user to assume the role for. Roles may not be used when specifying the and of an AWS root user.
For users and roles that require Multi-factor Authentication, specify the and connection properties. This will cause the CData Data Provider for Amazon Athena 2018 to submit the MFA credentials in a request to retrieve temporary authentication credentials. Note that the duration of the temporary credentials may be controlled via the (default 3600 seconds).
In addition to the and properties, specify , and . Set to the region where your Amazon Athena data is hosted. Set to a folder in S3 where you would like to store the results of queries.
If is not set in the connection, the data provider connects to the default database set in Amazon Athena.
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.
π Setting the Connection properties (Salesforce is shown.)After you create the data source, create the data source view.
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.
π Discovered relationships in the data source view (Salesforce is shown).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.
The last step before you can process the project and deploy Amazon Athena data to SSAS is creating the cubes.
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.
π Configuring the target server and database.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 Amazon Athena 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 Amazon Athena.
Download a free trial of the Amazon Athena Data Provider to get started:
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