Big Data on AWS

Course Features

Course Details

Description
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, Amazon QuickSight, Amazon Athena and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.

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 on Amazon EMR
Choose appropriate AWS data storage options
Identify the benefits of using Amazon Kinesis for near real-time big data processing
Leverage Amazon Redshift to efficiently store and analyze data
Comprehend and manage costs and security for a big data solution
Identify options for ingesting, transferring, and compressing data
Leverage Amazon Athena for ad-hoc query analytics
Leverage AWS Glue to automate ETL workloads.
Use visualization software to depict data and queries using Amazon QuickSight
Orchestrate big data workflows using AWS Data Pipeline

Intended Audience
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

Prerequisites
We recommend that attendees of this course have the following prerequisites:
Basic familiarity with big data technologies, including Apache Hadoop, 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 Essentials course or have equivalent experience
Basic understanding of data warehousing, relational database systems, and database design

Delivery Method
This course is 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.

Course Outline
This course covers the following concepts on each day:
Day 1
Overview of Big Data
Ingestion
Big Data streaming and Amazon Kinesis
Using Kinesis to stream and analyze Apache server logs
Storage Solutions
Querying Big Data using Amazon Athena
Using Amazon Athena to analyze log data
Introduction to Apache Hadoop and Amazon EMR

Day 2
Using Amazon Elastic MapReduce
Storing and Querying Data on DynamoDB
Hadoop Programming Frameworks
Processing Server Logs with Hive on Amazon EMR
Streamlining Your Amazon EMR Experience with Hue
Running Pig Scripts in Hue on Amazon EMR
Spark on Amazon EMR
Processing New York Taxi dataset using Spark on Amazon EMR

Day 3
Using AWS Glue to automate ETL workloads
Amazon Redshift and Big Data
Visualizing and Orchestrating Big Data
Visualizing
Managing Amazon EMR Costs
Securing Big Data solutions
Big Data Design Patterns
This course does not have any sections.

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