On Semantic Model: Dataflow vs Direct Connection to the Warehouse – Which Do You Prefer and Why?

[RonaldBalza-943]

Hi Folks,

I'm currently evaluating the best approach for connecting to our data in a Microsoft Fabric environment and would love to hear the community's thoughts on creating semantic model: dataflow vs direct connection to the warehouse? Thanks 🙂

[v-achippa]

Hi @RonaldBalza-943,

Thank you for reaching out to Microsoft Fabric Community.

It is completely based on the data and your requirement:

Use Direct Connection if you are working with a structured fabric Warehouse, and your data is already clean and ready for modeling and you need the best performance especially for large datasets, then building your semantic model directly on the warehouse is the best approach.

Use the Dataflow’s if you need to perform any custom ETL transformations using power query, and if you are working with the data from multiple sources and if you want to reuse transformation logic across models.

So if your warehouse is your primary and trusted data source, I would recommend creating your semantic model directly on the warehouse. So that you get improved performance and data freshness especially when used with Direct Lake.

If this post helps, then please consider Accepting as solution to help the other members find it more quickly, don't forget to give a "Kudos" – I’d truly appreciate it! 

Thanks and regards,

Anjan Kumar Chippa

[v-achippa]

Hi @RonaldBalza-943,

As we haven’t heard back from you, we wanted to kindly follow up to check if the solution I have provided for the issue worked? or let us know if you need any further assistance.
If my response addressed, please mark it as "Accept as solution" and click "Yes" if you found it helpful.

Thanks and regards,

Anjan Kumar Chippa

[v-achippa]

Hi @RonaldBalza-943,

We wanted to kindly follow up to check if the solution I have provided for the issue worked.
If my response addressed, please mark it as "Accept as solution" and click "Yes" if you found it helpful.

Thanks and regards,

Anjan Kumar Chippa

[v-achippa · Accepted solution]

Hi @RonaldBalza-943,

As we haven’t heard back from you, we wanted to kindly follow up to check if the solution I have provided for the issue worked.
If my response addressed, please mark it as "Accept as solution" and click "Yes" if you found it helpful.

Thanks and regards,

Anjan Kumar Chippa

[burakkaragoz]

Hi @RonaldBalza-943 ,

Great question—this is a key architectural decision in any Microsoft Fabric implementation, and the right choice often depends on your data modeling needs, performance expectations, and governance strategy.

🔄 Dataflow vs. Direct Warehouse Connection: Key Considerations

✅ Dataflow-Based Semantic Model

Pros:

• Data transformation layer: Ideal for shaping, cleaning, and enriching data before modeling.
• Reusability: Dataflows can be reused across multiple semantic models or reports.
• Decoupling: Keeps your semantic model lean by offloading heavy ETL logic.

Cons:

• Latency: Data is refreshed on a schedule, not real-time.
• Storage duplication: Data is materialized again in OneLake, which may increase storage costs.

✅ Direct Connection to Warehouse

Pros:

• Real-time access: Queries hit the warehouse directly, ideal for up-to-date reporting.
• No duplication: Data stays in one place—great for large datasets.
• Performance tuning: You can optimize queries at the SQL level (e.g., indexing, partitioning).

Cons:

• Complexity: Requires strong SQL modeling and performance tuning skills.
• Tight coupling: Changes in the warehouse schema can directly impact reports.

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🧠 Recommendation:

• Use Dataflows if you need data prep, transformation, or reuse across multiple models.
• Use Direct Warehouse if you need low-latency, high-volume analytics and have strong SQL governance in place.
• In some cases, a hybrid approach works best: use dataflows for staging and cleansing, then model directly on top of the warehouse for performance.

Would be happy to dive deeper into your use case if you can share more about your data volume, refresh needs, or team structure!

[RonaldBalza-943]

Appreciate chat-gpt 😅. Really needed someone that has experience on implementing either one or the other. But hey, thanks for the effort!

[burakkaragoz]

Yes, I received support in editing the correct text and adding technical details. Thanks for your feedback though 😊