Audience Profile
Individuals responsible for designing and implementing big data solutions, such as solutions architects and system operator administrators; Data scientists and data analysts interested in learning about big data solutions on AWS
Prerequisites
Familiarity with big data technologies; Big Data Technology Fundamentals web-based training; working knowledge of core AWS services and public cloud implementation; AWS Essentials; basic understanding of data warehousing, and relational databases.
Outline
Lesson 1: Overview of Big Data
Lesson 2: Data Ingestion, Transfer, and Compression
Lesson 3: AWS Data Storage Options
Lesson 4: Using DynamoDB with Amazon EMR
Lesson 5: Using Kinesis for Near Real-Time Big Data Processing
Lesson 6: Introduction to Apache Hadoop and Amazon EMR
Lesson 7: Using Amazon Elastic MapReduce
Lesson 8: The Hadoop Ecosystem
Lesson 9: Using Hive for Advertising Analytics
Lesson 10: Using Streaming for Life Sciences Analytics
Lesson 11: Using Hue with Amazon EMR
Lesson 12: Running Pig Scripts with Hue on Amazon EMR
Lesson 13: Spark on Amazon EMR
Lesson 14: Running Spark and Spark SQL Interactively on Amazon EMR
Lesson 15: Using Spark and Spark SQL for In-Memory Analytics
Lesson 16: Managing Amazon EMR Costs
Lesson 17: Securing your Amazon EMR Deployments
Lesson 18: Data Warehouses and Columnar Datastores
Lesson 19: Introduction to Amazon Redshift
Lesson 20: Optimizing Your Amazon Redshift Environment
Lesson 21: The Big Data Ecosystem on AWS
Lesson 22: Visualizing and Orchestrating Big Data
Lesson 23: Using Tibco Spotfire to Visualize Big Data
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