Big Data on AWS

  • Tuition USD $2,025 GSA  $1,670.03
  • Reviews star_rate star_rate star_rate star_rate star_half 552 Ratings
  • Course Code AWS-BIG-DATA
  • Duration 3 days
  • Available Formats Classroom, Virtual

Prerequisite Courses

Architecting on AWS
Developing on AWS
Systems Operations on AWS

Big Data on AWS 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. 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 Gained

This course teaches you how to:

  • 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
  • Secure 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 Can Benefit

This course is intended for:

  • 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

Prerequisites

We recommend that attendees of this course have the following prerequisites:

  • Basic familiarity with big data technologies, including Apache Hadoop, MapReduce, HDFS, and SQL/NoSQL querying
  • Students should complete the free Big Data Technology Fundamentals web-based training or have equivalent experience
  • Working knowledge of core AWS services and public cloud implementation
  • Basic understanding of data warehousing, relational database systems, and database design
  • Attended one of Architecting on AWS, Developing on AWS, or Systems Operations on AWS

Course Details

Day 1

  • 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

Day 2

  • 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

Day 3

  • 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

Note: course outline may vary slightly based on the regional location and/or language in which the class is delivered.

How do I enroll?

A comprehensive listing of ExitCertified courses can be found here. You can register directly for the required course/location when you select "register". If you have any questions or prefer to speak with an ExitCertified education consultant directly, please submit your query here. A representative will contact you shortly.

How do I pay for a class?

You can pay at the time of registration using credit card (Mastercard/Visa/American Express) cheque or PO.

What if I have training credits?

ExitCertified honors all savings programs from the partners we work with. ExitCertified also offers training credits across multiple partners through our FLEX Account.

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

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Instructor was great at engaging participants and when applicable tailoring content/discussion to projects we're currently working on. It's hard to keep a classroom engaged in a virtual environment but Stas did a great job.

Michael was great. He was patient and delivered material with analogies and showed deep interest in the content and our questions. He was one of few instructor that I love.,

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