Big Data on AWS

Master cloud-based big data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, create big data environments and leverage best practices to design big data environments for security and cost-effectiveness.

Level: Beginner

Duration: 3 days

Industry: Information Technology

About this course


Big Data on Amazon Web Services introduces you to cloud-based big data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and the rest of the AWS big data platform. Learn how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue.  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. Enroll in Big Data on Amazon Web Services today.

For more information about Big Data on Amazon Web Services, check this link on Amazon's website.

Who can benefit?


People who can benefit from this course are:

  • Individuals responsible for designing and implementing big data solutions, namely Solutions Architects
  • Data Scientists and Data Analysts interested in learning about the services and architecture patterns behind big data
    solutions on AWS

This is what you'll learn

  • Fit AWS solutions within a big data ecosystem
  • Leverage Apache Hadoop in the context of Amazon EMR
  • Identify components of an Amazon EMR cluster
  • Launch and configure an Amazon EMR cluster
  • Leverage 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
  • 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
  • Choose appropriate AWS data storage options

     Course Outline

  • Overview of Big Data
  • Big Data Ingestion and Transfer
  • Big Data Streaming and Amazon Kinesis
  • Lab 1: Using Amazon Kinesis to Stream and Analyze Apache Server Log Data
  • Big Data Storage Solutions
  • Big Data Processing and Analytics
  • Lab 2: Using Amazon Athena to Query Log Data From Amazon S3
  • 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 EMRWeb 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
  • Visualizing and Orchestrating Big Data
    Lab 7: Using TIBCO Spotfire to Visualize Data
  • Managing Big Data Costs
  • Securing Your Amazon Deployments
  • Big Data Design Patterns

Prerequisites

Architect - Architecting on AWS

Developer - Developing on AWS

Operations - Systems Operations on AWS

Contact P2L to schedule the dates for this course.

Start training and begin working towards one of the following certifications today.

Specialty
AWS Certified Data Analytics - Specialty

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