Data Environment Options

Hi icassiem 

Your situation: no data infrastructure, data in AWS (RDS/S3/MongoDB), API-only access, manual CSV exports today. Here's the short answer.
F2 (~$262/month) is your entire stack in one purchase:

Fabric Lakehouse — your storage (replaces needing Azure SQL or Dataverse)
Fabric Notebooks — your ETL (Python script that loops the API per client weekly, writes to Lakehouse)
Fabric Pipelines — your scheduler (automates the notebook runs)
Direct Lake — Power BI reads from Lakehouse with no import refresh needed
Copilot — AI narratives, natural language Q&A, DAX generation

You don't need Dataverse, Azure SQL, or to migrate off AWS. Just read from the product API and store results in Fabric Lakehouse.
Architecture:
Product API → Fabric Notebook (loops per client) → Lakehouse → Power BI + Copilot
If F2 is denied:
Use Power Automate (free with M365) to call the API weekly → write to SharePoint → Power BI reads from SharePoint on scheduled refresh. Less elegant but zero cost.
Pitch F2 as: "One subscription replaces separate ETL tools, a database, a scheduling platform, and gives us AI — 5 tools for $262/month."
Start with one client's API as a proof of concept.

https://learn.microsoft.com/en-us/fabric/data-engineering/lakehouse-overview
https://learn.microsoft.com/en-us/fabric/data-engineering/how-to-use-notebook
https://learn.microsoft.com/en-us/power-bi/create-reports/copilot-introduction
https://learn.microsoft.com/en-us/fabric/get-started/direct-lake-overview

Thanks 
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For more Power BI tips and discussions, let’s connect on LinkedIn:
https://www.linkedin.com/in/natarajan-manivasagan

Cheers!