Chris Bergh shares how to manage data quality and pipeline risk through implementing a ‘Mission Control’ center for DataOps
The Head of data got a call from the CEO of the entire company about a compliance report that was empty, with no data. So, he had to rally 26 different people across his team all-day And what was the problem? A field passed through the pipeline that was blank. Can you imagine how embarrassed he is at the error? How frustrated all those 26 people — most likely the best he has on his team — at having to chase a crappy error? And he has 1000 other pipelines in the same ‘hope it works’ position, just waiting for some customer to find a problem. High risk, indeed.
DataKitchen Named a Representative Vendor in the 2022 Gartner® Data and Analytics Essentials: #DataOps Report
“The goal of DataOps is to enable predictable delivery and change management of data and all data-related artifacts such as data pipelines, data models and semantics”