About this Course

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

Outline

  • Overview of Big Data
  • Data Ingestion, Transfer, and Compression
  • AWS Data Storage Options
  • Using DynamoDB with Amazon EMR
  • Using Kinesis for Near Real-Time Big Data Processing
  • Introduction to Apache Hadoop and Amazon EMR
  • Using Amazon Elastic MapReduce
  • The Hadoop Ecosystem
  • Using Hive for Advertising Analytics
  • Using Streaming for Life Sciences Analytics
  • Using Hue with Amazon EMR
  • Running Pig Scripts with Hue on Amazon EMR
  • Spark on Amazon EMR
  • Running Spark and Spark SQL Interactively on Amazon EMR
  • Using Spark and Spark SQL for In-Memory Analytics
  • Managing Amazon EMR Costs
  • Securing your Amazon EMR Deployments
  • Data Warehouses and Columnar Datastores
  • Introduction to Amazon Redshift
  • Optimizing Your Amazon Redshift Environment
  • The Big Data Ecosystem on AWS
  • Visualizing and Orchestrating Big Data
  • Using Tibco Spotfire to Visualize Big Data

Prerequisites

It's highly recommended that one earns their AWS Cloud Practioner or any other AWS certification.

Exam Details

AWS Exam: AWS Certified Big Data – Specialty

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