You can often add more value to your data by combining it with other sources to produce an enriched data set. By keeping large reference datasets out of the main Dataverse database you can dramatically reduce storage costs. You can then combine them as needed using Azure Data Factory.
In my last post I loaded some data from Excel into Azure Data Lake and stored it in the Common Data Model format. Now I want to present that data using Power BI.
Last time I showed how to create a data lake, but how do you get data into it? What format should you store it in?
In the world of data technologies, you’ll probably see data lakes appearing more and more often. I’d like to take a closer look at the Azure Data Lake and how it works with the wider Azure data ecosystem.
I’m pleased to announce that I’ve just released version 3 of SQL 4 CDS. The main updates in this release are: Metadata queries Support for virtual (___name) attributes