AWS Discovery Day
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AWS, Developer

BIG DATA ON AWS

Available Dates
Course Objectives
Prerequisites
Target Audience
Course Outline

Course Overview

In this course, you will learn about cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis, and the rest of the AWS big data platform. You will learn how to use Amazon EMR to process data using the broad ecosystem of Apache Hadoop tools like Hive and Hue. Additionally, you will learn how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.

The AWS Certified Big Data – Specialty certification training is intended for individuals who perform complex Big Data investigations with at least 2 years of experience using AWS technology. Big Data is an advanced certification and its best handled by students who have already gotten associate-level certification in AWS & have some real-world industry experience.

AWS Big Data certification won’t just assistance you become familiar with some new skills, it can position you for a higher paying job or help you transform your present role into a Big Data and Analytics professional.

 

Course Objectives

After completing this course, students will be able to:

  • Design & Maintain Big Data.
  • Execute core AWS Big Data services according to basic architecture best practices.
  • Leverage tools to automate data analysis.
  • Store big data with S3 & DynamoDB in a scalable, and secure manner.
  • Use the Hadoop ecosystem with AWS using Elastic MapReduce.
  • Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS & Aurora.
  • Visualize big data in the cloud using AWS QuickSight.
  • Process big data with AWS Lambda & Glue ETL.
  • Move & transform massive data streams with Kinesis.
  •  

Course Prequisites

 

  • Students hold an AWS Certified Cloud Practitioner or a current Associate-level certification: AWS Certified Solutions Architect – Associate, AWS Certified Developer – Associate or AWS Certified SysOps Administrator – Associate.
  • 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.

Target Audience

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

Experienced technologists looking certification in Big Data technologies on Amazon Web Services.

 

 

  • 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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What Our Students Have to Say

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I would recommend this course as it is up to date with the current release which is quite rare as things move on so fast. The classroom set up worked well and the labs were good and relevant to the course.’ – Oracle
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