[DataMasters] Getting Data Mastering at Scale Right
What's required to master large numbers of data sources? First, avoid approaches that require writing rules. Then use machine learning and cloud computing to efficiently handle the workload. That advice comes from Mike Stonebraker, a database pioneer who helped create the INGRES relational database system, won the 2014 A.M. Turing Award, and has co-founded several data management startups, including Tamr.
Mike, who's an adjunct professor of computer science at MIT, talks about common data mastering mistakes, why traditional tools aren't right for the task, and shares examples of companies that have successful mastered data at scale.
Brought to you by Ran Levi of DataMasters