Big Data on AWS

Course Modality

Instructor-led (classroom)

Course Level

Foundational

Course Time

5 days

Course Language

English

Course 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 environment for security and cost-effectiveness.

Prerequisites

  • Big Data Technology Fundamentals web-based training or equivalent experience.
  • AWS Technical Essentials course or equivalent experience.

Intended Audience

This course is intended for:

  • Experienced IT professionals who are already familiar with AWS services.
  • Individuals are responsible for designing and implementing big data solutions, namely Solutions Architects.
  • Data Scientists and Data Analysts interested in learning about big data solutions on AWS.

Why The DataTech Labs ?

Self-Paced Online Video

A 360-degree learning approach that you can adapt to your learning style

A 360-degree learning approach that you can adapt to your learning style

Engage and learn more with these live and highly-interactive classes alongside your peers

24/7 Teaching Assistance

24/7 Teaching Assistance Keep engaged with integrated teaching

Online Practice Labs

Projects provide you with sample work to show prospective employers.

Applied Projects

Real-world projects relevant to what you’re learning throughout the program

Learner Social Forums

A support team focused on helping you succeed alongside a peer community

Skill 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 and Pig.
  • Leverage Amazon Athena for ad hoc analytics
  • 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.
  • Introduce Amazon Athena for ad hoc analytics.
  • Leverage AWS Glue to automate ETL workloads.
  • Define data warehousing and columnar database concepts.
  • Leverage Amazon Redshift to efficiently store and analyze data.
  • Leverage Hue to improve the ease-of-use of Amazon EMR.
  • Comprehend and manage costs and security for your big data deployments.
  • Identify options for ingesting, transferring, and compressing data.
  • Use visualization software to depict data and queries.
  • Orchestrate big data workflows using AWS Data Pipeline.

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Course Curriculum

Overview of Big Data

Big Data Ingestion and Transfer

Big Data Streaming and Amazon Kinesis

Lab 1: Streaming and Processing Apache Server Logs using Amazon Kinesis

Big Data Storage Solutions

Big Data Processing and Analytics

Lab 2: Using Amazon Athena to Analyze Log Data

Apache Hadoop and Amazon EMR

Lab 3: Storing and Querying Data on Amazon DynamoDB

 

Using Amazon EMR

Hadoop Programming Frameworks

Lab 4: Processing Server Logs With Hive on Amazon EMR

Web Interfaces on Amazon EMR

Lab 5: Running Pig Scripts in Hue on Amazon EMR

Apache Spark on Amazon EMR

Lab 6: Processing NY Taxi Data Using Spark on Amazon EMR

Using AWS Glue to Automate ETL Workloads

Amazon Redshift and Big Data

Securing Your Amazon Deployments

Managing Big Data Costs

Visualizing and Orchestrating Big Data

Lab 7: Using TIBCO Spotfire to Visualize Data

Big Data Design Patterns

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