The data mesh concept is being touted as the next big thing in analytics data management. But is it just a rehash of distributed data access, data virtualization or data-as-a-service architectures, the data fabric, or the logical data warehouse concept? Or is there some there there? Is it really a new concept or just marketing lingo? Is the data mesh as-defined comprehensible, implementable, scalable, practical, adaptable? And how does it handle the critical tenets of data warehousing, i.e., subject-orientation, non-volatility, historicity, and time-variance? And what about dimensionality or handling slowly-changing-dimensions? Ultimately, is the data mesh a recipe for an architectural data mess?
Join our panel of data mensches to hash out the data mesh.
Data & Analytics Strategy Innovation Fellow, West Monroe
Director of Engineering, Starburst
Head of Data and Analytics, Kaiser Permanente
EVP & CDO, Vista