Mixed Model Arts - The Convergence of Data Modeling Across Apps, Analytics, and AI

Description For decades, data modeling has been fragmented by use cases: applications, analytics, and machine learning/AI. This leads to data siloing and “throwing data over the wall.” With the emergence of AI, streaming data, and “shifting left" are changing data modeling, these siloed approaches are insufficient for the diverse world of data use cases. Today's practitioners must possess an end-to-end understanding of the myriad techniques for modeling data throughout the data lifecycle. This presentation covers "mixed model arts," which advocates converging various data modeling methods and the innovations of new ones. Speaker Joe Reis, a seasoned data professional with over two decades of experience, is a globe-trotting author and speaker. Known as a "recovering data scientist," his expertise encompasses data engineering, architecture, and machine learning. He is highly sought-after as a keynote speaker at major data conferences worldwide, advising and investing in innovative data product companies. Additionally, he contributes regularly to his personal blog and Practical Data Modeling, and hosts popular data podcasts like "The Monday Morning Data Chat" and "The Joe Reis Show." In his spare time, Joe is passionate about authoring new books and articles, continuously striving to push the boundaries of the data industry.