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.
Download this paper to learn:
- How enterprises have applied three generations of AI to address data unification challenges
- How new advances have made data unification less time-intensive and more scalable
- What the future holds for the future of AI for data unification