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Tony Shan

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Big Data Pyramid

Though most big data projects are typically data-intensive, a pure data-driven approach is a big risk. These initiatives actually require multiple disciplines to implement a viable solution to complex business problems. A comprehensive method is necessary to tackle the big data issues and challenges systematically. The Big Data Pyramid is illustrated in the diagram below, which include the key constructs to capitalize the big data potentials along 4 aspects: Technology, Insights, People, and Process (TIPP).
  • Technology: Enabling Platform - a high-performance model of loosely-coupled components to process the full set of large volumes of structured and unstructured data in a scalable way. Both COTS and open source products should be leveraged to have a best-of-breed mix.
  • Insights: Business Value and Impacts - the big data undertakings must be pragmatic to transform the IT to a paradigm that demonstrates the tangible value to the business operations with competitive edges. Sophisticated patterns must be applied to gain insights that were "invisible" in the traditional approach.
  • People: Competency - advanced cross-disciplinary skills are need to implement complex big data initiatives. The combination of art, engineering and science skillsets will help big data become a new functional capability. The organization structure should be revamped to support cross-board activities and oversight.
  • Process: Lifecycle Management - end-to-end lifespan of data assets from sunrise to sunset. The automated process enables effective management of data quality, service, compliance, and security. Clear roles and responsibilities must be defined in a RACI matrix for the operations governance.

For more information, please contact Tony Shan ([email protected]).

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Tony Shan works as a senior consultant, advisor at a global applications and infrastructure solutions firm helping clients realize the greatest value from their IT. Shan is a renowned thought leader and technology visionary with a number of years of field experience and guru-level expertise on cloud computing, Big Data, Hadoop, NoSQL, social, mobile, SOA, BI, technology strategy, IT roadmapping, systems design, architecture engineering, portfolio rationalization, product development, asset management, strategic planning, process standardization, and Web 2.0. He has directed the lifecycle R&D and buildout of large-scale award-winning distributed systems on diverse platforms in Fortune 100 companies and public sector like IBM, Bank of America, Wells Fargo, Cisco, Honeywell, Abbott, etc.

Shan is an inventive expert with a proven track record of influential innovations such as Cloud Engineering. He has authored dozens of top-notch technical papers on next-generation technologies and over ten books that won multiple awards. He is a frequent keynote speaker and Chair/Panel/Advisor/Judge/Organizing Committee in prominent conferences/workshops, an editor/editorial advisory board member of IT research journals/books, and a founder of several user groups, forums, and centers of excellence (CoE).