Data Modeling Mastery for AI and Beyond

An inordinate amount of some of the most vital aspects of Artificial Intelligence--from data engineering to data science, data preparation to machine learning--rely on one indispensable prerequisite: data modeling. Without effective data modeling, organizations can't integrate data across sources to build advanced analytics models. Data modeling is foundational to assembling training datasets, utilizing specific data for end user applications, and scaffolding predictive cognitive computing models. Consequently, it behooves companies to make the modeling process as efficient as possible to achieve the following three benefits that optimize their modeling endeavors--and the advanced analytics applications and use cases they support. These advantages are difficult, if not impossible, to realize with traditional relational approaches to data modeling.