Getting Value from Big Data (Hadoop for Managers and Execs)


Executives, IT Managers and investors who want to learn about Hadoop and Big Data

Topics covered

Brave new world of Big Data, benefits, business opportunities, challenges, technologies, implementation stages


Interactive seminar followed with Q&A


One or two days, depending on the level of detail and hands-on work


  • Review Big Data challenges, potential and benefits
  • Understand Apache Hadoop, its role in Big Data and the roles of related technologies
  • Survey typical use cases in various industries
  • Get firm grip on phases of Big Data technologies adoption in the enterprise
  • Get a preview of the future of Hadoop and Big Data

Detailed outline

Big Data potential and benefits

    • What is Big Data?
    • Sources
    • Quantities
    • Challenges of processing
    • Technologies
    • Strategies
    • New ways of data thinking
    • Uses and benefits
    • Big Data players, their approaches
    • Untapped potential

Hadoop and Big Data technologies

    • History of Hadoop tools
    • Architectural Concepts
    • Who is using Hadoop
    • Hadoop skills and job market
    • Distributions and support
    • 8 use cases of how Hadoop can help you

Typical use cases in various industries/sectors (this section may be tailored).

    • Social networking
    • Marketing and advertising
    • Financial risk/insurance
    • Healthcare
    • Law enforcement
    • Sales and market analytics
    • Fraud detection
    • Litigation
    • Government and politics
    • Language, meaning, feeling
    • Human resources

Hadoop and Big Data adoption

    • Hadoop benefits: storage & processing
    • Hadoop ecosystem
    • Integration with Hadoop (BI tools, databases, visualization, etc.)
    • What is possible with Hadoop: batch analysis, real time analysis, analytics
    • Competing and complementing technologies (Oracle, IBM, Microsoft, etc.)
    • Planning adoption: use cases, pilot projects, implementations
    • Key challenges of adopting Hadoop / Big Data
    • Production and beyond
    • The role of iterative design and development

The Future of Big Data and Hadoop

    • Adoption trends
    • Hadoop developments and alternatives
    • What’s next for Big Data in general

Labs and demos (optional but recommended)

    • High-level Hadoop labs
    • Hive SQL labs
    • Spark labs as demo

Labs are optional but highly recommended. They are kept on the level that is high enough for managers and executives but nevertheless provide a good feel for the technologies.