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Big Data on AWS

Part of the AWS Certified Big Data–Specialty certification path

Designed for solutions architects, SysOps administrators, data analysts, and more, this course 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.

Full Description and Outline

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Description

Learn to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue in this hands-on course. You will also 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. 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
  • 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 Should Attend?

This course is intended for:

  • Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps Administrators.
  • Data Scientists and Data Analysts interested in learning about 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, 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 Essentials course or have equivalent experience.
  • Basic understanding of data warehousing, relational database systems, and database design.

Delivery Method

This course is delivered through a mix of:

  • Instructor-Led Training (ILT)
  • Hands-On Labs

Hands-On Activity

  • This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.
Questions? 929.777.8102 [email protected]
Course Outline

Day 1

  • Overview of Big Data
  • Ingestion
  • Big Data streaming and Amazon Kinesis
  • Using Kinesis to stream and analyze Apache server logs
  • Storage Solutions
  • Querying Big Data using Amazon Athena
  • Using Amazon Athena to analyze log data
  • Introduction to Apache Hadoop and Amazon EMR

Day 2

  • Using Amazon Elastic MapReduce
  • Storing and Querying Data on DynamoDB
  • Hadoop Programming Frameworks
  • Processing Server Logs with Hive on Amazon EMR
  • Streamlining Your Amazon EMR Experience with Hue
  • Running Pig Scripts in Hue on Amazon EMR
  • Spark on Amazon EMR
  • Processing New York Taxi dataset using Spark on Amazon EMR

Day 3

  • Using AWS Glue to automate ETL workloads
  • Amazon Redshift and Big Data
  • Visualizing and Orchestrating Big Data
  • Visualizing
  • Managing Amazon EMR Costs
  • Securing Big Data solutions
  • Big Data Design Patterns
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Don't see a date that fits your schedule? Contact us for scheduling options at 929.777.8102
Download Fact Sheet
Course Duration: 3 Days
Ways to Save

Software Summer School - BOGO - JUNE, JULY, & AUGUST CLASSES

Our Software Summer School is back in session! Buy One, Get One Free on our most popular live virtual training classes offered between June 1 and August 31, 2024. Take both classes yourself or split them with a colleague.

Our practical, hands-on courses can help you and your team in areas like AI, GitHub, agile, leadership, DevOps, software testing, and many more. Live virtual training allows you to dive deep into these topics with instructor-led classes from the comfort of your home or office.

Ready to join? Click the Register button below to register via email.

This is a limited time offer, and certain restrictions do apply. See details below.

OFFER DETAILS: Register for any participating live virtual class being offered in June, July, or August 2024 and get a second class of equal or lesser value free. Classes must take place between June 1 and August 31. Not all classes are valid. Contact Client Support for specifics on which classes are included. Register directly with our Client Support team at 929.777.8102 or through the email above. This offer is only valid for new registrations and cannot be combined with other promotions. Optional certification test vouchers must be purchased one per person who wishes to add them on and are NOT included in the Buy 1 Get 1 Free deal that is limited to just the class.
 
PREQUISITES: Many of our classes require previous skills, experience, or certifications to ensure understanding. Please be sure to check prerequisites for each class to ensure you have the experience necessary to actively participate. Questions? Call us at 929.777.8102.
 
Choose from the following classes.  (✔ = Guaranteed to run dates):
 
June Classes

July Classes

August Classes

 
  

 
Description

Learn to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue in this hands-on course. You will also 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. 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
  • 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 Should Attend?

This course is intended for:

  • Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps Administrators.
  • Data Scientists and Data Analysts interested in learning about 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, 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 Essentials course or have equivalent experience.
  • Basic understanding of data warehousing, relational database systems, and database design.

Delivery Method

This course is delivered through a mix of:

  • Instructor-Led Training (ILT)
  • Hands-On Labs

Hands-On Activity

  • This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.
Questions? 929.777.8102 [email protected]
Course Outline

Day 1

  • Overview of Big Data
  • Ingestion
  • Big Data streaming and Amazon Kinesis
  • Using Kinesis to stream and analyze Apache server logs
  • Storage Solutions
  • Querying Big Data using Amazon Athena
  • Using Amazon Athena to analyze log data
  • Introduction to Apache Hadoop and Amazon EMR

Day 2

  • Using Amazon Elastic MapReduce
  • Storing and Querying Data on DynamoDB
  • Hadoop Programming Frameworks
  • Processing Server Logs with Hive on Amazon EMR
  • Streamlining Your Amazon EMR Experience with Hue
  • Running Pig Scripts in Hue on Amazon EMR
  • Spark on Amazon EMR
  • Processing New York Taxi dataset using Spark on Amazon EMR

Day 3

  • Using AWS Glue to automate ETL workloads
  • Amazon Redshift and Big Data
  • Visualizing and Orchestrating Big Data
  • Visualizing
  • Managing Amazon EMR Costs
  • Securing Big Data solutions
  • Big Data Design Patterns

Bring this course to your team at your site. Contact us to learn more at 929.777.8102.

✓ = Guaranteed to Run
Dates
Mode
Location
Price
Call to Schedule
Anytime
On-Site / Private
Your Location
Your Location
Request a Quote
Contact Us
Download Fact Sheet
Course Duration: 3 Days
Description

Learn to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue in this hands-on course. You will also 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. 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
  • 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 Should Attend?

This course is intended for:

  • Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps Administrators.
  • Data Scientists and Data Analysts interested in learning about 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, 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 Essentials course or have equivalent experience.
  • Basic understanding of data warehousing, relational database systems, and database design.

Delivery Method

This course is delivered through a mix of:

  • Instructor-Led Training (ILT)
  • Hands-On Labs

Hands-On Activity

  • This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.
Questions? 929.777.8102 [email protected]
Course Outline

Day 1

  • Overview of Big Data
  • Ingestion
  • Big Data streaming and Amazon Kinesis
  • Using Kinesis to stream and analyze Apache server logs
  • Storage Solutions
  • Querying Big Data using Amazon Athena
  • Using Amazon Athena to analyze log data
  • Introduction to Apache Hadoop and Amazon EMR

Day 2

  • Using Amazon Elastic MapReduce
  • Storing and Querying Data on DynamoDB
  • Hadoop Programming Frameworks
  • Processing Server Logs with Hive on Amazon EMR
  • Streamlining Your Amazon EMR Experience with Hue
  • Running Pig Scripts in Hue on Amazon EMR
  • Spark on Amazon EMR
  • Processing New York Taxi dataset using Spark on Amazon EMR

Day 3

  • Using AWS Glue to automate ETL workloads
  • Amazon Redshift and Big Data
  • Visualizing and Orchestrating Big Data
  • Visualizing
  • Managing Amazon EMR Costs
  • Securing Big Data solutions
  • Big Data Design Patterns

Questions?

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