What problems does the “modern data stack” actually solve that have not been solved already?
Help an old guy out here! I have been working in the data warehousing / business intelligence field for the last 25 years. I have probably been exposed to every traditional technology under the sun. I am honestly having a really hard time understanding what the big deal is with the whole data lake / Serverless X / spark / airflow / metric store / etc. It seems to me that these technologies are geared towards use cases that either involve data volumes that most companies will never reach or reinvent stuff that already exists (how is a metric store any different than an OLAP cube with calculations?) What is it that’s so great that’s not solved by a file system, traditional ETL and a RDBMS?
