Trends in Data Architecture - A DATAVERSITY 2017 Report


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About the Paper

The old paradigms of Data Architecture are evolving at an ever-increasing rate. Past enterprise architectures are undergoing significant technological changes in the face of new trends, including Big Data, non-relational data stores, Blockchain, Internet of Things, Machine Learning and Artificial Intelligence, Data Lakes, and many others. Enterprises must still contend with their foundational data assets and legacy systems though – Data Governance, Master Data Management, Data Quality, Data Modeling, and other traditional Data Management concepts and practices are more important than ever.

What are the emerging trends in Data Architecture? How can next generation architectures help an enterprise to become data-driven? How does an organization implement such changes and still maintain their core data assets? What ecosystems are being employed most by organizations? Which ones are planned for the future? How are organizations coping with these changes?

Produced by:

Data Education for Business and IT Professionals