Getting data from Dynamics 365 Business Central to put them in Fabric

[pmscorca]

Hi,

in order to get data from a Dynamics 365 Business Central solution to put them in a Fabric lakehouse it seems that the method better is to use Dataverse between Business Central and Fabric.
I don't know how getting data from Business Central to Dataverse and if the table data load is full or incremental and if a load date or a modified date is added.
Well, any helps to me, please? Many thanks

[v-pagayam-msft]

Hi @pmscorca ,

Just checking in — did the solution provided help resolve your issue?
If yes, please consider marking it as the accepted answer so it can help others facing a similar challenge.
Thank you.

[pmscorca]

Hi, thanks for your reply.

Using the bc2adls tool it seems a bit complex to do.

I'm trying to a recap about bringing data from a Dynamics 365 Business Central solution into a Fabric lakehouse:

1. from Dynamics 365 Business Central to Fabric --> Business Central supports native integration with Dataverse. The data loading into Datavers is a synchronization process. In Dataverse the BC tables are represented as virtual tables (similar to view concept);
2. from Dataverse to Fabric --> in Dataverse it is possible to use the Link to Fabric, that is a Power Apps feature. The data remain in Dataverse and the link is represented as a Fabric shortcut; no ETLs or copies is necessary to bring Dataverse data into Fabric, so why using a data pipeline or a dataflow gen2? A such Data Factory feature could be used after that the Dataverse data are virtually entered in Fabric to manage a full or incremental load from a first lakehouse to a second (destination) lakehouse.

Ultimately, it seems that the Business Central data remain in BC and it is important to know the existence of a modified date or a load date in order to manage an incremental load. Moreover it is important to know how BC manages the Dataverse integration (as a replica of entire tables?).

It could be useful to have a Dataverse mirroring or a Business Central mirroring in Fabric.

[v-pagayam-msft]

Hi @pmscorca ,

You are right.BC integrates with Dataverse using virtual tables, but these may not be directly used in Fabric shortcuts unless materialized. To analyze or load data incrementally, you may need to replicate the data into physical Dataverse tables.

Shortcuts work for real-time access (only with physical tables).

Use Dataflows Gen2 or Data Factory for full/incremental loads and historical tracking.

Many BC tables have LastModifiedDateTime or similar fields for incremental logic.

For true mirroring, BC data should first be materialized in Dataverse, then linked or loaded into Fabric.

Hope this helps!
Thank you.

[pmscorca]

Hi, thanks for your reply.

I try to write two good practices in order to bring BC data into Fabric.

First practice:

1. from BC to Dataverse --> the BC data are physically copied in Dataverse (how?);
2. from Dataverse to Fabric --> the Link to Fabric feature is used to bring Dataverse data in a lakehouse by a shortcut.

Second practice:

1. from BC to Dataverse --> the native integration with Dataverse is used. The BC data remain in BC and they are exposed in Dataverse as a view object;
2. from Dataverse to Fabric --> the Dataverse data are physically copied in a Fabric lakehouse by Data Factory.

About the mirroring solution I meant a mirroring for Dataverse as a specific Fabric feature.

Which is the better practice between the two ones described above?

Following the first practice, is it better to manage a full load from BC to Dataverse and an incremental load from Dataverse to Fabric, using the LastModifiedDateTime column?

Following the second practice, is it better to manage a full load from the first Fabric lakehouse and an incremental load from it to a second lakehouse, using the LastModifiedDateTime column?

Thanks

[v-pagayam-msft]

Hi @pmscorca ,
Yes, it’s better to do a full load from BC to Dataverse (with table replication enabled), then an incremental load from Dataverse to Fabric using LastModifiedDateTime. Shortcuts only work with physical tables. Refer the link here
Hope this helps.
Thank you.

[pmscorca]

Hi, the first practice represents is the best practice to bring BC data into Fabric, isn't it?

Using the Link to Fabric feature from Dataverse to Fabric means creating a shortcut: so, why managing an incremental physical load from Dataverse to Fabric?

Thanks

[v-pagayam-msft · Accepted solution]

Hi @pmscorca ,
The first approach is recommended, provided that BC data is physically replicated in Dataverse. With Link to Fabric, a shortcut is created, so there is no need for incremental loading from Dataverse to Fabric ,the data remains in Dataverse and is simply referenced in Fabric. Incremental loading is only necessary if you are physically copying the data, such as for staging or historical tracking purposes.
Hope this helps.If so, consider accepting it as solution.

Thank you.

[v-pagayam-msft]

Hi @pmscorca ,
Thank you for reaching out to us on Microsoft Fabric Community Forum!

To bring data from Dynamics 365 Business Central into a Microsoft Fabric Lakehouse, it is recommended to first integrate Business Central with Dataverse, and then ingest the data into Fabric using Dataflows Gen2 or Data Factory pipelines. Business Central supports native integration with Dataverse via the Admin Center, where core tables like Customer, Items, and Sales can be synced ,some as virtual tables. Once the data is in Dataverse, you may use Power Query or pipelines to load it into a Lakehouse. For more details, refer to these resources.
Solved: How to integrate business central data to fabric o... - Microsoft Fabric Community
Introduction to Microsoft Fabric and Business Central - Business Central | Microsoft Learn
Set up your Dataverse connection - Microsoft Fabric | Microsoft Learn
Real-time data warehousing with Microsoft Dataverse and Fabric zero-copy integration - Microsoft Pow...

Hope this helps.If so,give us kudos and consider accepting it as solution.

Regards,
Pallavi G.