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AWS Big Data

AWS Certified Big Data – Specialty

Course Overview

Big Data on AWS, you will learn about cloud-based Big Data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and the rest of the AWS Big Data platform. We will show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue. We will 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.
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Course Information

Course Fee - $2,495

  • 5 Days Instructor-led Training
  • Attend Class - Online or In Person
  • Free Retake Upto 2 Years
  • Study Materials Included
AWS Cloud Infrastructure
AWS Cloud Infrastructure

Upcoming Schedules

There are no up-coming events

What You Will Learn?

    • 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 and Spark SQL on Amazon EMR
    • Choose appropriate AWS data storage options
    • Identify the benefits of using Amazon Kinesis for near real-time big data processing
    • Define data warehousing and columnar database concepts
    • Leverage Amazon Redshift to efficiently store and analyze data
    • Comprehend and manage costs and security for Amazon EMR and Amazon Redshift 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

    Outline

    Day 1

    • Overview of Big Data
    • Ingestion, Transfer, and Compression
    • Storage Solutions
    • Storing and Querying Data on DynamoDB
    • Big Data Processing and Amazon Kinesis
    • Introduction to Apache Hadoop and Amazon EMR
    • Using Amazon Elastic MapReduce

    Day 2

    • Hadoop Programming Frameworks
    • Processing Server Logs with Hive on Amazon EMR
    • Processing Chemistry Data Using Hadoop Streaming on Amazon EMR
    • Streamlining Your Amazon EMR Experience with Hue
    • Running Pig Scripts in Hue on Amazon EMR
    • Spark on Amazon EMR
    • Interactively Creating and Querying Tables with Spark and Spark SQL on Amazon EMR
    • Managing Amazon EMR Costs
    • Securing your Amazon EMR Deployments

    Day 3

    • Data Warehouses and Columnar Datastores
    • Amazon Redshift and Big Data
    • Optimizing Your Amazon Redshift Environment
    • Big Data Design Patterns
    • Visualizing and Orchestrating Big Data
    • Using Tibco Spotfire to Visualize Big Data

    Lab Outline

    Contact us for full outline

    Pre-Requisites

    • Basic familiarity with big data technologies, including Apache Hadoop, MapReduce, 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 Technical Essentials (AWSE) course or have equivalent experience
    • Basic understanding of data warehousing, relational database systems, and database design

    Why you choose us

    A Global Name In Cisco and AWS Training
    • Published 10 Computer Based Training Materials

      We are the only Canadian company that has in-house published Video books on Cisco Training that are sold from $799 to $1599

    • Free Retake of Any course Up to 2 years
    • 24/7 Access to Facility & Lab
    • Mentor Ship Program
    • Get Experience Certificate
    • We Train US Army, Navy and Air Force
    US Air Force
    US Air Force

    Contact Us

    •  1810 E. Sahara Ave. Suite 223, Las Vegas, NV, 89104, USA
    • +1-437-913-9405
    • Contact Us
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