Big Data on AWS

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.





ADDRESS
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CATEGORIES
NextGen Skills

Course Objectives

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.

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

Target Audience and Prerequisites

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.
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.

Course Content

+ 1 - Overview of Big Data
  • 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
+ 2 - Using Hive for Advertising Analytics
  • 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
+ 3 - Using Amazon Kinesis for Real-Time Big Data Processing
  • 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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