- 4 hours
This course is designed to introduce and guide the user through the three phases associated with big data - obtaining it, processing it, and analyzing it. The Introduction to Big Data module explains what big data is, its attributes and how organizations can benefit from it. It also provides a snapshot of job roles, and available certification and training, in order to forge a career in big data. The Hadoop Fundamentals module explains how the Apache Hadoop environment is designed to store and process big data, and introduces Apache products such as MapReduce, YARN, Spark and Tez, while the Basic Analytics module provides an overview of different types of analytics and describes how organizations can benefit from them.
The initial module is suitable for any IT professional needing an overview of big data and the benefits it can provide to organizations. Later modules are specifically aimed at Programmers, Administrators and Data Analysts needing to manage, process, and analyze big data.
A basic understanding of the type of data used, and available within your industry.
After completing this course, the student should be able to:
- Describe the characteristics of Big Data
- Identify the benefits of implementing a Big Data strategy
- Explain how Hadoop is used to store, manage, and process Big Data
- Identify the different types of analytics and describe how they are used
What is Big Data and how did it Evolve?
Structured and Unstructured Data
Big Data Attributes
Big Data Lifecycle
Big Data Infrastructure
Job Roles, Certification, and Training for Big Data Careers
The Purpose of Apache Hadoop
Complimentary Apache Products
Real-Life Hadoop Examples
Hadoop in the Cloud
Hadoop Distributed File System (HDFS)
Using MapReduce to Process Big Data
Hadoop and the Mainframe
How Analytical Data is Used to Benefit Organizations
Descriptive, Diagnostic, Predictive, and Prescriptive Analytics
How Businesses are Using Analytics
Batch and Real-Time Analytics
Leading Analytic Solution Providers and their Products