This course is an introduction to Big Data. The course explains key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. The course explains how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. It also introduces key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages.
Bachelor of Computer Science - 144 CRs
Thomas Erl, Wajid Khattak, Paul Buhler, Big Data Fundamentals: Concepts, Drivers & Techniques, Pearson
content serial | Description |
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1 | Big Data Concepts and Terminology |
2 | Big Data Characteristics |
3 | Different Types of Data |
4 | Business Motivations and Drivers for Big Data Adoption |
5 | Big Data Analytics Lifecycle |
6 | Big Data BI |
8 | Data Visualization for Big Data |
9 | Big Data Storage Concepts |
10 | Big Data Processing Concepts |
11 | Big Data Analysis Techniques |
13 | Big Data Analysis Techniques |
14 | Projects Discussion |
15 | Revision |
7 | 7th Week Exam |
12 | 12th Week Exam |
16 | Final Exam |
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