Big Data on Amazon Web Services

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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, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.
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.
Participants should complete the AWS Essentials course or have equivalent experience: http://www.professional.ie/it_training_courses/AWS_Technical_Essentials-4628.htm
Basic understanding of data warehousing, relational database systems, and database design
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
Day 1:
Overview of Big Data, Apache Hadoop, and the Benefits of Amazon EMR
Amazon EMR Architecture
Using Amazon EMR
Launching and Using an Amazon EMR Cluster
Hadoop Programming Frameworks
Day 2:
Using Hive for Advertising Analytics
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
Data Ingestion, Transfer, and Compression
Using Amazon Kinesis for Real-Time Big Data Processing
Day 3:
Using Amazon Kinesis and Amazon EMR to Stream and Process Big Data
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