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Big Data on AWS

Learn how to build and leverage best practices for big data solutions on AWS.

GK# 4509

Course Overview

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In this course, you will learn about cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis, and the rest of the AWS big data platform. You will learn how to use Amazon EMR to process data using the broad ecosystem of Apache Hadoop tools like Hive and Hue. Additionally, you will learn how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.

Schedule

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What You'll Learn

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  • Apache Hadoop in the context of Amazon EMR
  • The architecture of an Amazon EMR cluster
  • Launch an Amazon EMR cluster using an appropriate Amazon Machine Image and Amazon EC2 instance types
  • Appropriate AWS data storage options for use with Amazon EMR
  • Ingesting, transferring, and compressing data for use with Amazon EMR
  • Use common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming
  • Work with Amazon Redshift to implement a big data solution
  • Leverage big data visualization software
  • Appropriate security options for Amazon EMR and your data
  • Perform in-memory data analysis with Spark and Shark on Amazon EMR
  • Options to manage your Amazon EMR environment cost-effectively
  • Benefits of using Amazon Kinesis for big data

Outline

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Virtual Classroom Live Outline

1. Overview of Big Data

2. Data Ingestion, Transfer, and Compression

3. AWS Data Storage Options

4. Using DynamoDB with Amazon EMR

5. Using Kinesis for Near Real-Time Big Data Processing

6. Introduction to Apache Hadoop and Amazon EMR

7. Using Amazon Elastic MapReduce

8. The Hadoop Ecosystem

9. Using Hive for Advertising Analytics

10. Using Streaming for Life Sciences Analytics

11. Using Hue with Amazon EMR

12. Running Pig Scripts with Hue on Amazon EMR

13. Spark on Amazon EMR

14. Running Spark and Spark SQL Interactively on Amazon EMR

15. Using Spark and Spark SQL for In-Memory Analytics

16. Managing Amazon EMR Costs

17. Securing your Amazon EMR Deployments

18. Data Warehouses and Columnar Datastores

19. Introduction to Amazon Redshift

20. Optimizing Your Amazon Redshift Environment

21. The Big Data Ecosystem on AWS

22. Visualizing and Orchestrating Big Data

23. Using Tibco Spotfire to Visualize Big Data

 

Note: This is an emerging technology course. Course outline is subject to change as needed.

Labs

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Virtual Classroom Live Labs

This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises

Prerequisites

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  • Familiarity with big data technologies, including Apache Hadoop and HDFS
  • Knowledge of big data technologies such as Pig, Hive, and MapReduce is helpful but not required
  • Working knowledge of core AWS services and public cloud implementation
  • Students should complete the AWS Essentials course or have equivalent experience
  • Basic understanding of data warehousing, relational database systems, and database design

Who Should Attend

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  • Individuals responsible for designing and implementing big data solutions, such as solutions architects and system operator administrators
  • Data scientists and data analysts interested in learning about big data solutions on AWS
Course Delivery

This course is available in the following formats:

Virtual Classroom Live

Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.

Duration: 3 day

Request this course in a different delivery format.
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