To bring the Finance and Operations data to the modern data warehouse architecture, Finance and Operations has introduced a new feature that allows us to move the Entity store that was previously in the Azure SQL database to a customer's own Azure Data Lake. Setting up Entity store integration with Azure Data Lake is a simple one-time setup that can be done under System parameters, as shown in the following screenshot:

Once this feature has been enabled, aggregate measurements are staged in Azure Data Lake in CDM folder format. The Azure Data Lake integration feature also supports incremental exports, which means data in Azure Data Lake can be frequently updated.

As shown in the following diagram, you can use the Azure Factory to bring other external data sources into Azure Data Lake, perform cleansing, transformation, and machine learning, and load data into Azure Synapse Analytics. From there on, you can build Power BI reports and embed them back into Finance and Operations analytical workspaces or consume them using the Power BI service:

For customers who do not have the need to use the full stack of Azure Synapse Analytics, they can simply use Power BI Dataflow to connect to the Entity store CDM folder or use the SQL On-Demand feature to build Power BI reports.

The Entity store in Azure Data Lake is a good model; however, it still has the following shortcomings:

• The Entity Store feature only exports aggregate measurement data in Azure Data Lake.
• Creating and modifying aggregate measurements or start schemas is a development effort in Finance and Operation.
• To integrate data entities with a data warehouse, BYOD technology has to be used.

Now let's deep dive into a part of the future roadmap (at the time of writing) that Microsoft has announced.