Big Data on AWS


Big Data on AWS

Description

Big Data on AWS introduces you to cloud-based big data solutions and Amazon Elastic MapReduce (EMR), 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 Pig and Hive. We also teach you how to create big data environments, work with Amazon DynamoDB and Amazon Redshift, understand the benefits of Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.

Course Objectives

This course is designed to teach you how to:

  • Understand Apache Hadoop in the context of Amazon EMR
  • Understand the architecture of an Amazon EMR cluster
  • Launch an Amazon EMR cluster using an appropriate Amazon Machine Image and Amazon EC2 instance types
  • Choose appropriate AWS data storage options for use with Amazon EMR
  • Know your options for 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
  • Choose appropriate security options for Amazon EMR and your data
  • Perform in-memory data analysis with Spark and Shark on Amazon EMR
  • Choose appropriate options to manage your Amazon EMR environment cost-effectively
  • Understand the benefits of using Amazon Kinesis for big data

Intended Audience

This course is intended for:

  • Partners and customers responsible for implementing big data environments, including:
    • Data Scientists
    • Data Analysts
    • Enterprise, Big Data Solution Architects

Prerequisites

We recommend that attendees of this course have:

  • Basic 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

Delivery Method

This course will be delivered through a mix of:

  • Instructor-Led Training (ILT)
  • Hands-on Labs

Hands-On Activity

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

Duration

  • 3 Days

Course Outline

This course will cover the following concepts on each day:

 

Day 1

  • Overview of Big Data and Apache Hadoop
  • Benefits of Amazon EMR
  • Amazon EMR Architecture
  • Using Amazon EMR
  • Launching and Using an Amazon EMR Cluster
  • High-Level Apache Hadoop Programming Frameworks
  • Using Hive for Advertising Analytics

Day 2

  • Other Apache Hadoop Programming Frameworks
  • Using Streaming for Life Sciences Analytics
  • Overview: Spark and Shark for In-Memory Analytics
  • Using Spark and Shark for In-Memory Analytics
  • Managing Amazon EMR Costs
  • Overview of Amazon EMR Security
  • Exploring Amazon EMR Security
  • Data Ingestion, Transfer, and Compression

Day 3

  • Using Amazon Kinesis for Real-Time Big Data Processing
  • AWS Data Storage Options
  • Using DynamoDB with Amazon EMR
  • Overview: Amazon Redshift and Big Data
  • Using Amazon Redshift for Big Data
  • Visualizing and Orchestrating Big Data
  • Using Tableau Desktop or Jaspersoft BI to Visualize Big Data

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