Big Data 101
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Get started with Big Data fundamentals. Learn the key concepts, tools, and technologies used to analyze and manage large datasets in modern data ecosystems.
At a Glance
How big is big and why does big matter and what does Apache Hadoop have to do with it? In this course you will see the Big Data big picture and you will learn the terminology used in Big Data discussions.
About This Course
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
Course Syllabus
- 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 – BDUse 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
General Information
- This course is self-paced.
- It can be taken at any time.
- It can be audited as many times as you wish.
Recommended skills prior to taking this course
- None
Requirements
- None
Course Staff
Fireside Analytics Inc.
Shingai Manjengwa (@Tjido) is the Director of Insights and Analytics at Fireside Analytics Inc. An NYU Stern alum, she graduated from the Stern Business Analytics Masters program in 2014 and founded Fireside Analytics the following year. Fireside Analytics is a data analytics consulting company that makes data analytics and data science skills accessible to private sector companies, non-profits and education institutions. Fireside Analytics works with clients to build their data science capabilities and train their staff and stakeholders using customized case studies. Connect with us on Facebook, Twitter 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 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
Leons Petrazickis was the Ombud for Hadoop content on Skills Network as well as the Platform Architect for Skills Network 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.
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