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AWS-BIGDAT – Big Data on AWS

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Big Data on AWS introduces students 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. In this course, students will learn how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue. Students 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.

Course Outline:

Course Outline

This course covers the following concepts on each day:

Day 1

  • Overview of Big Data
  • Ingestion
  • Big Data streaming and Amazon Kinesis
  • Using Kinesis to stream and analyze Apache server logs
  • Storage Solutions
  • Querying Big Data using Amazon Athena
  • Using Amazon Athena to analyze log data
  • Introduction to Apache Hadoop and Amazon EMR

Day 2

  • Using Amazon Elastic MapReduce
  • Storing and Querying Data on DynamoDB
  • Hadoop Programming Frameworks
  • Processing Server Logs with Hive on Amazon EMR
  • Streamlining Your Amazon EMR Experience with Hue
  • Running Pig Scripts in Hue on Amazon EMR
  • Spark on Amazon EMR
  • Processing New York Taxi dataset using Spark on Amazon EMR

Day 3

  • Using AWS Glue to automate ETL workloads
  • Amazon Redshift and Big Data
  • Visualizing and Orchestrating Big Data
  • Visualizing
  • Managing Amazon EMR Costs
  • Securing Big Data solutions
  • Big Data Design Patterns

Course Audience & Prerequisites:

Audience:

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.

Course Offerings:

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.

  • Course Outline
  • Course Audience & Prerequisites
  • Course Offerings
  • Related Courses

Course Outline

This course covers the following concepts on each day:

Day 1

  • Overview of Big Data
  • Ingestion
  • Big Data streaming and Amazon Kinesis
  • Using Kinesis to stream and analyze Apache server logs
  • Storage Solutions
  • Querying Big Data using Amazon Athena
  • Using Amazon Athena to analyze log data
  • Introduction to Apache Hadoop and Amazon EMR

Day 2

  • Using Amazon Elastic MapReduce
  • Storing and Querying Data on DynamoDB
  • Hadoop Programming Frameworks
  • Processing Server Logs with Hive on Amazon EMR
  • Streamlining Your Amazon EMR Experience with Hue
  • Running Pig Scripts in Hue on Amazon EMR
  • Spark on Amazon EMR
  • Processing New York Taxi dataset using Spark on Amazon EMR

Day 3

  • Using AWS Glue to automate ETL workloads
  • Amazon Redshift and Big Data
  • Visualizing and Orchestrating Big Data
  • Visualizing
  • Managing Amazon EMR Costs
  • Securing Big Data solutions
  • Big Data Design Patterns

Audience:

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.

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.