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southgrad10
Helper II
Helper II

SSAS in Fabric

We use Microsoft Dynamics 365 Business Central (BC) and want to use Fabric.  Our team is more T-SQL driven that Python.  It seems that since our data is structured in tables coming from BC via API that we should simply load the data to a Fabric Warehouse.  Currently, we use SSIS to transform the data and SSAS tabular model (cube) to further manipulate to source Power BI reports.  How would I replicate the tabular model that we use in SSAS?  Plus, should we consider using a Lakehouse, instead of a Warehouse?

1 ACCEPTED SOLUTION
v-nikhilan-msft
Community Support
Community Support

Hi @southgrad10 
Thanks for using Fabric Community.

It sounds like you’re considering a significant shift in your data architecture, and I’m here to help guide you through this process. Let’s break down your questions:
Replicating SSAS Tabular Model in Microsoft Fabric: Microsoft Fabric doesn’t directly support SSAS Tabular Models. You can copy and paste from the Expression Window in SSAS into Power Query in Power BI Desktop. Then, use Tabular Editor to copy and paste the measures between your SSAS and Power BI Desktop.
The only thing you would need to create is the relationships. You can also use Azure Data Factory to manage the data migration directly between databases.

1. Leverage Data Warehouse (DW):

  • This cloud-based data warehouse acts as the central data store for your BC data.
  • Utilize ADF to extract and transform data from BC and load it into Warehouse.
  • Create a tabular model within warehouse using its Tabular Data Model feature. This enables similar functionality to your SSAS model, including dimensions, measures, and calculations.
  • Connect Power BI directly to Data Warehouse for visualizations and reporting.

2. Explore Power BI Premium Per User (PPU):

  • If your data volume and user base are manageable, consider PPU.
  • Import your SSAS model directly into Power BI, replicating its structure and logic.
  • This approach eliminates the need for a separate modeling tool but might impose user license limitations.


Using a Warehouse or a Lakehouse in Microsoft Fabric: Microsoft Fabric offers both Warehouse and Lakehouse options. The choice between the two depends on your specific needs and the skill set of your team. If your team is more familiar with SQL, then using a Warehouse might be easier. Creating, altering, and dropping tables, and insert, update, and delete operations are only supported in Warehouse in Microsoft Fabric, not in the SQL analytics endpoint of the Lakehouse.
On the other hand, a Lakehouse might be a good option if you have more advanced data science or business intelligence scenarios that require richer data engineering or data integration. A key part of Microsoft Fabric offering is OneLake, a single, unified, logical data lake for the whole organization.  The SQL analytics endpoint enables you to query data in the Lakehouse using T-SQL language.

For more information please refer to these links:
Fabric decision guide - choose a data store - Microsoft Fabric | Microsoft Learn
Microsoft Fabric: Should I Use a Data Warehouse or Lakehouse? - Purple Frog Systems
T-SQL surface area - Microsoft Fabric | Microsoft Learn
Better together - the lakehouse and warehouse - Microsoft Fabric | Microsoft Learn


I hope this helps. Please let me know if you have any further questions.

View solution in original post

2 REPLIES 2
v-nikhilan-msft
Community Support
Community Support

Hi @southgrad10 
Thanks for using Fabric Community.

It sounds like you’re considering a significant shift in your data architecture, and I’m here to help guide you through this process. Let’s break down your questions:
Replicating SSAS Tabular Model in Microsoft Fabric: Microsoft Fabric doesn’t directly support SSAS Tabular Models. You can copy and paste from the Expression Window in SSAS into Power Query in Power BI Desktop. Then, use Tabular Editor to copy and paste the measures between your SSAS and Power BI Desktop.
The only thing you would need to create is the relationships. You can also use Azure Data Factory to manage the data migration directly between databases.

1. Leverage Data Warehouse (DW):

  • This cloud-based data warehouse acts as the central data store for your BC data.
  • Utilize ADF to extract and transform data from BC and load it into Warehouse.
  • Create a tabular model within warehouse using its Tabular Data Model feature. This enables similar functionality to your SSAS model, including dimensions, measures, and calculations.
  • Connect Power BI directly to Data Warehouse for visualizations and reporting.

2. Explore Power BI Premium Per User (PPU):

  • If your data volume and user base are manageable, consider PPU.
  • Import your SSAS model directly into Power BI, replicating its structure and logic.
  • This approach eliminates the need for a separate modeling tool but might impose user license limitations.


Using a Warehouse or a Lakehouse in Microsoft Fabric: Microsoft Fabric offers both Warehouse and Lakehouse options. The choice between the two depends on your specific needs and the skill set of your team. If your team is more familiar with SQL, then using a Warehouse might be easier. Creating, altering, and dropping tables, and insert, update, and delete operations are only supported in Warehouse in Microsoft Fabric, not in the SQL analytics endpoint of the Lakehouse.
On the other hand, a Lakehouse might be a good option if you have more advanced data science or business intelligence scenarios that require richer data engineering or data integration. A key part of Microsoft Fabric offering is OneLake, a single, unified, logical data lake for the whole organization.  The SQL analytics endpoint enables you to query data in the Lakehouse using T-SQL language.

For more information please refer to these links:
Fabric decision guide - choose a data store - Microsoft Fabric | Microsoft Learn
Microsoft Fabric: Should I Use a Data Warehouse or Lakehouse? - Purple Frog Systems
T-SQL surface area - Microsoft Fabric | Microsoft Learn
Better together - the lakehouse and warehouse - Microsoft Fabric | Microsoft Learn


I hope this helps. Please let me know if you have any further questions.

Thank you so much for this information.  I will reach out if I have further questions.  Thanks for the quick reply!

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