Migrating OLAP Data Cubes to Azure Analysis Services: A Step-by-Step Guide

By GptWriter

783 words

Migrating OLAP Data Cubes to Azure Analysis Services: A Step-by-Step Guide

Are you looking to migrate your multidimensional database (OLAP data cube) from SQL Server Analysis Services to Azure Analysis Services? You may have come across the surprising fact that Azure Analysis Services does not support multidimensional models. But don’t worry, in this blog post, we will explore the reasons behind this limitation and provide you with a step-by-step guide on how to migrate your OLAP data cube to an equivalent tabular model in Azure Analysis Services.

Why Azure Analysis Services Doesn’t Support Multidimensional Models

Microsoft’s decision to not support multidimensional models in Azure Analysis Services is driven by several factors. One of the main reasons is the architectural differences between multidimensional and tabular models. Multidimensional models are based on the Multidimensional Expressions (MDX) language and have been around for a long time. On the other hand, tabular models are based on the Data Analysis Expressions (DAX) language and provide a more modern and flexible approach to data modeling.

By focusing on tabular models, Microsoft can leverage the performance and scalability benefits of the underlying VertiPaq engine, which is optimized for in-memory columnar storage. Tabular models also provide better integration with other Azure services, such as Power BI and Azure Machine Learning.

Converting OLAP Data Cubes to Tabular Models

To migrate your OLAP data cube to Azure Analysis Services, you will need to convert it into an equivalent tabular model. Here are the steps you can follow:

  1. Assess your OLAP data cube: Before starting the migration process, it’s important to assess your OLAP data cube and understand its structure, dimensions, measures, and calculations. This will help you plan the conversion process effectively.

  2. Design the tabular model: Based on the assessment of your OLAP data cube, design the equivalent tabular model in Azure Analysis Services. Identify the tables, columns, relationships, and measures that need to be included in the tabular model.

  3. Create the tabular model: Using tools like SQL Server Data Tools (SSDT) or Power BI Desktop, create a new tabular model project and start building the tabular model based on your design. Define the tables, columns, relationships, and measures in the model.

  4. Import data into the tabular model: Once the tabular model structure is defined, import the data from your OLAP data cube into the tabular model. You can use tools like SQL Server Integration Services (SSIS) or Azure Data Factory to extract data from the OLAP data cube and load it into the tabular model.

  5. Validate and optimize the tabular model: After importing the data, validate the tabular model to ensure that it accurately represents the data from the OLAP data cube. Optimize the model by defining appropriate relationships, hierarchies, and calculations to improve query performance.

  6. Deploy the tabular model to Azure Analysis Services: Once the tabular model is ready, deploy it to Azure Analysis Services. You can use tools like SQL Server Management Studio (SSMS) or Azure Portal to deploy the model to your Azure Analysis Services instance.

  7. Test and validate the migrated tabular model: After deploying the tabular model, test it thoroughly to ensure that it behaves as expected. Validate the query results, calculations, and performance to make sure that the migrated model meets your requirements.

Alternative Options for Deploying OLAP Data Cubes on Azure

If you prefer to continue using OLAP data cubes and want to deploy them on Azure, there are alternative options available:

  1. Azure Virtual Machines: You can create Azure Virtual Machines and install SQL Server Analysis Services on them to host your OLAP data cubes. This option provides more flexibility and control over your environment but requires managing the infrastructure yourself.

  2. Azure Stack: Azure Stack allows you to deploy Azure services on-premises or in a hybrid cloud environment. You can use Azure Stack to host SQL Server Analysis Services and deploy your OLAP data cubes.

  3. Third-party cloud services: There are third-party cloud services available that support OLAP data cubes on Azure. These services provide managed OLAP solutions and take care of the infrastructure and maintenance for you.

Conclusion

Migrating OLAP data cubes from SQL Server Analysis Services to Azure Analysis Services may require converting them into tabular models. While Azure Analysis Services does not support multidimensional models, tabular models offer a modern and scalable approach to data modeling. By following the step-by-step guide provided in this blog post, you can successfully migrate your OLAP data cube to Azure Analysis Services. Alternatively, you can explore other options like Azure Virtual Machines, Azure Stack, or third-party cloud services to deploy your OLAP data cubes on Azure.

Remember, the key to a successful migration is thorough planning, understanding your data cube structure, and validating the migrated model. Happy migrating!