1819: Data Observability: Monitor, Identify & Solve Silent Data Issues
I recently discovered a Belgian company called Soda who focuses on data quality monitoring and testing. Think of it a bit like application or software monitoring which is now ubiquitous. Soda scans for issues caused by human error, firmware upgrades, schema changes, cross-platform integration snafus, bought data, or transformation bugs. The aim is to automate, verify, and validate the flow of data from various sources and encourage collaboration between software/data engineers and downstream business decision-makers. The big idea here is to eliminate so-called ‘silent data issues.’ These are the issues that bubble up (hence the name Soda!) further downstream having gone undetected in datasets. In an era when most companies are moving towards being entirely data-driven, ensuring data is of the optimum quality is critical. I invited Soda CEO and founder Maarten Masschelein on the Tech Talks Daily to learn more. Maarten discusses why data quality monitoring is becoming a hot topic and provides examples of where bad data has caused serious problems. I also learn how Soda was listed as a data management Cool Vendor by Gartner.
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