PM9: From Big Data to STAR Data

This tutorial presents the trending shift from Big Data to Smart, Thing, Augmented, and Relevant (STAR) Data and discusses the anatomy of the STAR Data (5W+1H). The concept of Big Data is still linked with the 3Vs model defined in 2001. A number of products have been incubated and matured in the last 15 years to process large data sets, so that bigness has no longer become the only pressing problem. This presentation investigates the imperatives to make the paradigm shift to other core issues in today’s data world and pinpoints the trending of the top concerns in the new era: Smart, Thing, Augmented, and Relevant (STAR) Data.

We anatomize the STAR Data in a multi-dimensional way: What, Why, Where, Who, When and How (5W+1H), addressing the concepts, rationales, use cases, players, timing, and technology enablement. Further, we discuss the best practices of Convert, Condense, Converge, and Convince (C4) as the interdisciplinary guidelines for implementing real-life STAR Data projects. Working examples and use cases will be articulated, along with the technology enablement, during the session.

Tony Shan is a renowned visionary and thought leader incubating and nurturing interdisciplinary practice and enablement on emerging technologies like IoT, big data, cloud, and bots. He drives large-scale transformations of the most complex information systems at Fortune 500 companies. He leads pragmatic innovation for enterprise digitization in consulting.

He serves as an editor and on the advisory board of journals, as the chair of events, and as a judge in IT competitions. He speaks and organizes in various conferences and has authored hundreds of publications. As an intrapreneur/entrepreneur, he also founded several startups and user groups/forums.