WHAT YOU'LL LEARN

• Apache Hadoop in the context of Amazon EMR
• The architecture of an Amazon EMR cluster
• Launch an Amazon EMR cluster using an appropriate Amazon Machine Image and Amazon EC2 instance types
• Appropriate AWS data storage options for use with Amazon EMR
• Ingesting, transferring, and compressing data for use with Amazon EMR
• Use common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming
• Work with Amazon Redshift to implement a big data solution
• Leverage big data visualization software
• Appropriate security options for Amazon EMR and your data
• Perform in-memory data analysis with Spark and Shark on Amazon EMR
• Options to manage your Amazon EMR environment cost-effectively
• Benefits of using Amazon Kinesis for big data

Course Taught by AWS Instructors

As an AWS authorized, worldwide training partner you can trust that you're learning the latest content developed by AWS when taking a class with Global Knowledge. We have more than 12 Authorized AWS Instructors (AAI) who not only have real-world experience, but also go through a rigorous process to validate their teaching expertise.

COURSE OUTLINE

1. Overview of Big Data
2. Data Ingestion, Transfer, and Compression
3. AWS Data Storage Options
4. Using DynamoDB with Amazon EMR
5. Using Kinesis for Near Real-Time Big Data Processing
6. Introduction to Apache Hadoop and Amazon EMR
7. Using Amazon Elastic MapReduce
8. The Hadoop Ecosystem
9. Using Hive for Advertising Analytics
10. Using Streaming for Life Sciences Analytics
11. Using Hue with Amazon EMR
12. Running Pig Scripts with Hue on Amazon EMR
13. Spark on Amazon EMR
14. Running Spark and Spark SQL Interactively on Amazon EMR
15. Using Spark and Spark SQL for In-Memory Analytics
16. Managing Amazon EMR Costs
17. Securing your Amazon EMR Deployments
18. Data Warehouses and Columnar Datastores
19. Introduction to Amazon Redshift
20. Optimizing Your Amazon Redshift Environment
21. The Big Data Ecosystem on AWS
22. Visualizing and Orchestrating Big Data
23. Using Tibco Spotfire to Visualize Big Data

This is an emerging technology course. Course outline is subject to change as needed.

CALENDAR

Check out our Schedule of upcoming sessions delivery dates for this course.

LANGUAGE

Sessions will be held in spanish. English option available for private sessions.

PREREQUISITES

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

• Familiarity with big data technologies, including Apache Hadoop and HDFS
• Knowledge of big data technologies such as Pig, Hive, and MapReduce is helpful but not required
• Working knowledge of core AWS services and public cloud implementation
• Students should complete the AWS Essentials course or have equivalent experience
• Basic understanding of data warehousing, relational database systems, and database design

RELATED CERTIFICATIONS

AWS Certified Data Analytics Specialty

The average salary of an AWS-certified IT professional is roughly $114,000 – placing it in the top five highest-paying certifications. Read more about "What It Takes To Earn a Top-Paying AWS Certification".

FOLLOW-ON COURSES

If you are planning to certify, this exam preparation course will drive there you easily:

*Exam Readiness: AWS Certified Data Analytics Specialty

Also, depending on your role, some of the following specialty trainings may help you to deepen your knowledge and skills in the field:

*Data Warehousing on AWS

*Deep Learning on AWS

*The Machine Learning Pipeline on AWS

*Planning and Designing Databases on AWS