Cognitive Class

Big Data 101

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  • Course Number
  • Classes Start
    Any time, Self-paced
  • Estimated Effort
    3 hours
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Get answers to fundamental questions such as: What is Big Data? How do we tackle Big Data? Why are we interested in it? How does Big Data add value to businesses?

  • Gain insights on how to run better businesses and provide better services to customers
  • Get recommendations on how to process big data on platforms that can handle the volume, velocity, variety and veracity of Big Data
  • Learn why Hadoop is a great Big Data solution and why it's not the only Big Data solution


Module 1 - What is Big Data?

  • Characteristics of Big Data

  • What are the V’s of Big Data?

  • The Impact of Big Data

Module 2 - Big Data - Beyond the Hype

  • Big Data Examples

  • Sources of Big Data

  • Big Data Adoption

Module 3 - The Big Data and Data Science

  • The Big Data Platform

  • Big Data and Data Science

  • Skills for Data Scientists

  • The Data Science Process

Module 4 - Use Cases

  • Big Data Exploration

  • The Enhanced 360 View of a Customer

  • Security and Intelligence

  • Operations Analysis

Module 5 - Processing Big Data

  • Ecosystems of Big Data

  • The Hadoop Framework


  • This Big Data course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.


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Shingai Manjengwa, author of What is Big Data?

Fireside Analytics Inc.

Shingai Manjengwa (@Tjido) is the CEO of  Fireside Analytics Inc., an ed-tech start-up that develops customized online and in-person courses to teach digital literacy, data science, data visualization, and coding to high school students, policymakers, senior executives, small business owners, and working professionals. Data Science courses by Fireside Analytics have over 300,000 registered learners on platforms like IBMs and Coursera.An IBM Influencer and Author, Shingai has a Masters in Business Analytics from NYU Stern. Shingai is also the founder of Fireside Analytics Academy, a registered private high school (BSID: 886528) that teaches high school students to solve problems with data. What is Data Science? Data Science is the process of ethically acquiring, engineering, analyzing, visualizing and ultimately monetizing data. Connect with us on FacebookTwitter and LinkedIn. This course has been adapted from the original version created by Glen R.J. Mules (below), a Senior Instructor and Principal Consultant with IBM Information Management World-Wide Education.


Glen R.J. Mules

Glen R.J. Mules

Glen R.J. Mules is a Senior Instructor and Principal Consultant with IBM Information Management World-Wide Education and works from New Rochelle, NY. Glen joined IBM in 2001 as a result of IBM's acquisition of Informix Software. He has worked at IBM, and previously at Informix Software, as an instructor, a course developer, and in the enablement of instructors worldwide. He teaches courses in BigData (BigInsights and Streams), Optim, Guardium, and DB2, and Informix databases. He has a BSc in Mathematics from the University of Adelaide, South Australia; an MSc in Computer Science from the University of Birmingham, England; and has just completed a Ph.D. in Education (Educational Technology) at Walden University. His early work life was as a high school teacher in Australia. In the 1970s he designed, programmed, and managed banking systems in Manhattan and Boston. In the 1980's he was a VP in Electronic Payments for Bank of America in San Francisco and New York. In the early 1990's he was an EVP in Marketing for a software development company and chaired the ANSI X12C Standards Committee on Data Security for Electronic Data Interchange (EDI).


Leons Petrazickis photo

Leons Petrazickis

Leons Petrazickis is the Ombud for Hadoop content on IBM Big Data U as well as the Platform Architect for Big Data U Labs. As a senior software developer at IBM, he uses Ruby, Python, and Javascript to develop microservices and web applications, as well as manage containerized infrastructure.