Big Data on AWS

Learn to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue in this hands-on course. You will also learn 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
• 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

Who Should Attend?

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.