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Big Data Capability Model | @ThingsExpo #BigData #IoT #InternetOfThings

A capability model is a structure that represents the core abilities and competencies of an entity to achieve its objectives

A capability model is a structure that represents the core abilities and competencies of an entity (department, organization, person, system, and technology) to achieve its objectives, especially in relation to its overall mission and functions.

The Big Data Capability Model (BDCM) is defined as the key functionalities in dealing with Big Data problems and challenges.



It describes the major features, behaviors, practices and processes in an organization, which can reliably and sustainably produce required outcomes for Big Data demands. BDCM consist of the following elements:

  • Collection: collect raw data, sources, formats, discovery, protocols, staging
  • ELT: extract, load and transform data
  • Store: NoSQL repository, key-value, column-based, document-oriented, graph, Hadoop, MPP, in-memory, cache
  • Integration: data move, messaging, consumption, access, connector
  • Processing: parallel data processing, query, reporting, formatting, API, programming model
  • Analysis: analytics, slice and dice, data mining, classification, patterns, statistics
  • Decisioning: insights, machine learning, BI, recommendation, inference, prediction, business value
  • Service: data services, business services, process orchestration, knowledge, NFR
  • Presentation: display, visualization, dashboard, mobility, channels, collaboration, exploration
  • Storage: physical store, physical file system, logical file system, nodes, clustering, replication, backup, DR, archive, file encryption, disk encryption, data field masking
  • Management: quality, lifecycle, data assets, monitoring, metering, billing, job scheduling, access control, SLA, ROI
  • Governance: information policy, privacy, security, metadata, PMO, risk, TCO

For more information, please contact Tony Shan (TonyShan@live.com

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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).

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