AI - Big Data and Hadoop
Duration
3 hours
Overview
Description
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, Apache Spark and Tez.
Audience
This course is suitable for any IT professional needing an overview of big data and the benefits it can provide to organizations.
Prerequisites
A basic understanding of the type of data used, and available within your industry.
Objectives
- After completing this course, the student will be able to identify:
- 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
Course Content
Introduction to Big Data
Hadoop Fundamentals
The Purpose of Apache Hadoop
Hadoop Evolution
Hadoop Components
Complimentary Apache Products
Hadoop Distributions
Real-Life Hadoop Examples
Hadoop in the Cloud
Hadoop Distributed File System (HDFS)
Using MapReduce to Process Big Data
YARN