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Getting Value from Big Data

Hadoop for Managers and Execs

Course Code

BD62

Duration

1 Day

None
Brave new world of Big Data, benefits, business opportunities, challenges, technologies, implementation stages. This course is an interactive seminar followed by Q&A.

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. Course can be expanded to two days depending on labs and participants goals.
This course is designed for Executives, IT Managers and investors who want to learn about Hadoop and Big Data.

In this course, participants will:

  • 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
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
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