If you’re new to cloud data platforms, then you may be wondering what is the difference between a Data Lake vs Data Warehouse. You may hear these terms and think they are interchangeable. While both are used for data storage, they are quite different and serve different purposes.
Recently, I had a conversation with a product leader of a SaaS organization who shared how many of their customers don’t use the built-in analytics they offer as part of their product and instead ask them for direct access to their data. Their customers prefer to load the data into their own data warehouse or …
Though we were working on developer tools and developer run times, we were working closely with the SQL Server team. We were thinking about how we can enable people to write store procedures in .NET. In fact, one of the tools people can use against SQL Server came from our team.
Similarly for Azure, we ended up building all the developer tools and some of the run times for Azure as well. One of the advantages of being a developer at Microsoft is that you get to work with pretty much every platform team inside the company because you are sort of the glue that brings developers together on top of the platform.
There’s a lot of water under the bridge in the BI space. It has been a very challenging space to work in and solve problems. It’s a complicated beast. The problems are not simple, and there are many problems to solve. The volume of data is growing, the complexity of data is increasing, the speed of data is increasing… so I think all of those things come together to form the perfect storm of complexity, which is very difficult to solve.
But therein lies massive opportunity.