Data management strategy is boring, right? More to the point, it’s a solved problem. The relational model, SQL, and data warehouses date to the 1980s. I mean, what could be less strategic than the “what,” “how,” and “why” of an enterprise data management strategy? Build some pipelines and ETL jobs. Define a relational schema to cover big chunks of the business and drive analytics off the data warehouse OLAP cube queries. Easy right?
Not so fast. There’s no one to blame here since the conventional approach to data integration — based entirely on moving and copying data and leveraging data location in the storage layer — was until very recently the only game in town. The way we integrate data caused the data mess to begin with and the longer we stick with it, the worse the problem will become.
Read the rest of the article by CEO Kendall Clark on The New Stack here.
