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mild_heart
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Getting data into lakehouse from Planetary Computer

How to bring all Planetary Computer catalog data for a specific region into Microsoft Fabric Lakehouse?

Hi everyone, I’m currently working on something where I need to bring all available catalog data from the Microsoft Planetary Computer into a Microsoft Fabric Lakehouse, but I want to filter it for a specific region or area of interest.

I’ve been looking around, but I’m a bit stuck on how to approach this.

I have tried to get data into lakehouse using notebook by using python scripts (with the use of pystac-client, Planetary-computer, adlfs), I have loaded it as .tiff file.

But i wnat to ingest all catalog data for the particular region, is there any bulk data ingestion methodbfor this?

Is there a way to do this using Fabric’s built-in tools, like a native connector or pipelin?

Can this be done using the STAC API and some kind of automation, maybe with Fabric Data Factory or a Fabric Notebook?

What’s the best way to handle large-scale ingestion for a whole region? Is there any bulk loading approach that people are using?

Also, any tips on things like storage format, metadata, or authentication between the Planetary Computer and OneLake would be super helpful.

And, finally is there any ways to visualize it in powee bi? (currently planning to use it in web app, but is there any possibility of visualization in power bi?)

I’d love to hear if anyone here has tried something similar or has any advice on how to get started!

Thanks in advance!

TLDR: trying to load all Planetary Computer data for a specific region into lakehouse. Looking for best approachs

1 REPLY 1
lbendlin
Super User
Super User

The Planetary Computer Data Catalog includes petabytes of environmental monitoring data, in consistent, analysis-ready formats. All of the datasets below can be accessed via Azure Blob Storage.

Set up your Azure Blob Storage connection - Microsoft Fabric | Microsoft Learn

 

Note: "all" = "petabytes".  Even if you use shortcuts this can easily overwhelm your budget.

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