Course Overview
Duration: 3 Days
Big Data on AWS introduces you to cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis and the rest of the AWS big data platform. In this course, we show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue. We also teach you 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.

Note: We are an authorized reseller for AWS.

 

Who Should Attend
This course is intended for:

Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps Administrators
Data Scientists and Data Analysts interested in learning about big data solutions on AWS

 

Course Certifications
This course is part of the following Certifications:

 

Prerequisites
We recommend that attendees of this course have the following prerequisites:

Basic familiarity with big data technologies, including Apache Hadoop, MapReduce, HDFS, and SQL/NoSQL querying

Students should complete the Big Data Technology Fundamentals web-based training or have equivalent experience

Working knowledge of core AWS services and public cloud implementation

Students should complete the AWS Technical Essentials course or have equivalent experience

Basic understanding of data warehousing, relational database systems, and database design

 

Course Objectives
This course teaches you how to:

Fit AWS solutions inside of a big data ecosystem
Leverage Apache Hadoop in the context of Amazon EMR\Identify the components of an Amazon EMR cluster
Launch and configure an Amazon EMR cluster
Leverage common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming
Leverage Hue to improve the ease-of-use of Amazon EMR
Use in-memory analytics with Spark and Spark SQL on Amazon EMR
Choose appropriate AWS data storage options
Identify the benefits of using Amazon Kinesis for near real-time big data processing
Define data warehousing and columnar database concepts
Leverage Amazon Redshift to efficiently store and analyse data
Comprehend and manage costs and security for Amazon EMR and Amazon Redshift deployments
Identify options for ingesting, transferring, and compressing data
Use visualisation software to depict data and queries
Orchestrate big data workflows using AWS Data Pipeline

 

Course Content
Note: course outline may vary slightly based on the regional location and/or language in which the class is delivered.

Day 1

Overview of Big Data

Ingestion, Transfer, and Compression

Storage Solutions

Storing and Querying Data on DynamoDB

Big Data Processing and Amazon Kinesis

Introduction to Apache Hadoop and Amazon EMR

Using Amazon Elastic MapReduce

Day 2

Hadoop Programming Frameworks

Processing Server Logs with Hive on Amazon EMR

Processing Chemistry Data Using Hadoop Streaming on Amazon EMR

Streamlining Your Amazon EMR Experience with Hue

Running Pig Scripts in Hue on Amazon EMR

Spark on Amazon EMR

Interactively Creating and Querying Tables with Spark and Spark SQL on Amazon EMR

Managing Amazon EMR Costs

Securing your Amazon EMR Deployments

Day 3

Data Warehouses and Columnar Datastores

Amazon Redshift and Big Data

Optimising Your Amazon Redshift Environment

Big Data Design Patterns

Visualizing and Orchestrating Big Data

Using Tibco Spotfire to Visualise Big Data