Escaping Analysis Paralysis For Your Data Platform With Data Virtualization - Episode 107
With the constant evolution of technology for data management it can seem impossible to make an informed decision about whether to build a data warehouse, or a data lake, or just leave your data wherever it currently rests. What's worse is that any time you have to migrate to a new architecture, all of your analytical code has to change too. Thankfully it's possible to add an abstraction layer to eliminate the churn in your client code, allowing you to evolve your data platform without disrupting your downstream data users. In this episode AtScale co-founder and CTO Matthew Baird describes how the data virtualization and data engineering automation capabilities that are built into the platform free up your engineers to focus on your business needs without having to waste cycles on premature optimization. This was a great conversation about the power of abstractions and appreciating the value of increasing the efficiency of your data team.