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BG 201 – Enterprise Big Data Management

Duration: 3 – 4 days

This workshop will offer a methodology for creating and implementing an enterprise information management program, including the requirements of big data.

Data center

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Description

Although many organizations have instituted some form of enterprise data / information management programs, they have not included “big data” into those programs for various reasons.

Enterprise Information Management (EIM) is the set of business processes, disciplines and practices used to manage the information created from an organization’s data as an enterprise asset. EIM functions ensure that high quality information is available, protected, controlled and effectively leveraged to meet the knowledge needs of all enterprise stakeholders, in support of the enterprise mission. Big data must be included in any EIM / enterprise data management program for the initiative to be truly effective. Without incorporating the concepts, practices and nuances appropriate for big data management, organizations will be unable to take advantage of the value that these high-volume, high-velocity data sets can bring to decision making.

This workshop will offer a methodology for creating and implementing an enterprise information management program, including the requirements of big data. The attendee will gain an understanding of the importance of enterprise information management, the various types of information management components and proven approaches to the establishment of an enterprise information management program with the aspects of big data as an integral part of the approach. In this course, attendees will develop a plan for implementing an enterprise information management program that incorporates big data administration. Through case studies and team interaction, attendees will attain the real-world implementation skills necessary to build a successful strategy for big data enterprise information management program that will inform any organization’s approach to big data management.

Objectives

  • Understand the foundation of sharing data assets across entire organization – enterprise information management
  • Big data’s role as a component of enterprise information management
  • Comprehend the concepts of “big data” – volume, variety, velocity, veracity
  • Develop a big data EIM strategy – components and rationale
  • Learn how to manage expanding information requirements through a methodology for big data management
  • Understand the importance of central data management to an organization, and including big data management
  • Explain the importance of EIM in big data quality, big data integrity, big data reuse
  • Measure the value of enterprise information management for big data

Seminar Content

  • Information as a Enterprise Asset
    • Business value of managing data and information
    • Definitions
  • Enterprise Information Management – Introduction
    • What is EIM?
    • EIM framework
    • Big Data as part of EIM framework
    • EIM goals
    • EIM guiding principles
    • Issues and challenges of implementing an EIM program
    • Key attributes to a successful EIM program
    • The EIM organization structure
  • Introduction to EIM Framework Components
    • Data governance
    • Information architecture
    • Information quality management
    • Reference & master data management
    • Data warehousing & business intelligence
    • Structured data management
    • Unstructured data management
    • Metadata management
    • Information security management
  • Implementing a Enterprise Information Management Program
    • Defining EIM requirements for big data
    • Identifying data and metadata sources for big data
    • Approaches to EIM implementation – roadmap approach
    • Creating the EIM organization structure – EIM Center of Excellence
    • Relationship between the EIM organization and data governance
    • Creating the EIM project plan
    • EIM program artifacts for big data
    • EIM Maturity and Assessment Model
    • EIM technologies overview for big data management
    • EIM component artifact relationships & dependencies
    • Measuring EIM program success
    • Future of EIM and big data
  • Workshop conclusion
    • Summary, additional exercises, sources for further reading, etc.

About the Instructor

Dr. David P. Marco, PhD, Fellow IIM, CBIP, CDP is best known as the world’s foremost authority on data governance and metadata management. He is an internationally recognized expert in the fields of CDO, data management, data literacy, and advanced analytics. He has earned several industry honors, including Crain’s Chicago Business “Top 40 Under 40”, named by DePaul University as one of their “Top 14 Alumni Under 40”, and he is a Professional Fellow in the Institute of Information Management. Dr. Marco is the author of two widely acclaimed, best-selling books on metadata management.

David M00790 pp

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