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In today’s post, I want to talk about designing a data flow for a warehousing situation. I’ll refer to the reference cloud-based data warehouse data flow architecture that Microsoft has published which you’ll see in the image below.
I want to talk about the idea of taking data from our source systems and storing it in file storage. The diagram indicates we’d do this in blob storage. We sometimes prefer using Azure Date Lake, but regardless, the data is still being extracted from a source and put into files which are then loaded into the data warehouse.
I’m frequently asked, why would I store my data in files? For instance, if my source data is coming from a relational database, maybe pulling from an ERP system, why would I take data from that system, store it in files and then load it to my data warehouse?
Let me point out some reasons why:
So, these are some key reasons/benefits to help you understand why you may want to store data in files prior to loading it into the data warehouse. As I’m asked about this a lot, I hope you found this useful. If you have questions about data warehousing in Azure, cloud data platforms or anything Azure related, you’re in the right place. Click the link below or contact us—we’re here to help.
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