By Michael Stonebraker
Regardless of industry, data unification is a major challenge in any data analytics pipeline. In fact, data scientists spend up to 80% of their time locating data, unifying it from multiple sources, and cleaning it before they can even begin their real work. As enterprises increasingly seek to use information to gain a competitive advantage, they are looking for better ways to complete the data unification process. This paper will explore how enterprises have applied three generations of artificial intelligence (AI) to address this issue, as well as how new advances have made data unification less time-intensive and more scalable.