Overview

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.

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.

Skills Covered

  • 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

  • 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.

Course Curriculum

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-TE: AWS Technical Essentials course or have equivalent experience.
  • Basic understanding of data warehousing, relational database systems, and database design.

Not sure where to start? Check out our latest AWS Training and Certifications blog post.

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Course Modules

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Training Options

Intake: 17-19 Jan 2022
Duration: 3 Days
Guaranteed: TBC
Modality: ILT
Price:

RM5,400.00Enroll Now

RM6,690.00Enroll Now

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Intake: 17-19 Jan 2022
Duration: 3 Days
Guaranteed: TBC
Modality: VILT
Price:

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Exam:
Intake: 28-30 Mar 2022
Duration: 3 Days
Guaranteed: TBC
Modality: ILT
Price:

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RM6,690.00Enroll Now

Exam:
Intake: 28-30 Mar 2022
Duration: 3 Days
Guaranteed: TBC
Modality: VILT
Price:

RM5,400.00Enroll Now

RM6,690.00Enroll Now

Exam:
Intake: 30 May - 1 Jun 2022
Duration: 3 Days
Guaranteed: TBC
Modality: ILT
Price:

RM5,400.00Enroll Now

RM6,690.00Enroll Now

Exam:
Intake: 30 May - 1 Jun 2022
Duration: 3 Days
Guaranteed: TBC
Modality: VILT
Price:

RM5,400.00Enroll Now

RM6,690.00Enroll Now

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Exam & Certification

AWS Certified Data Analytics – Specialty.

Earn an industry-recognized credential from AWS that validates your expertise in AWS data lakes and analytics services. Build credibility and confidence by highlighting your ability to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. Show you have breadth and depth in delivering insight from data.

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