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An introduction to Amazon Elastic MapReduce (EMR) showing the available tools that can be used with Amazon EMR and the process of creating a cluster. A demonstration of how to create a cluster with Amazon EMR is covered.
An introduction to Amazon Elastic MapReduce (EMR) showing the available tools that can be used with Amazon EMR and the process of creating a cluster. A demonstration of how to create a cluster with Amazon EMR is covered.
Register for this course and see more details by visiting:
OpenCourser.com/course/3b2074/introduction
What's inside
Syllabus
Introduction to Amazon Elastic MapReduce (EMR)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces Cloud Computing and Hadoop concepts
Goes in-depth on creating clusters
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Save Introduction to Amazon Elastic MapReduce (EMR) to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Amazon Elastic MapReduce (EMR) with these
activities:
Follow AWS EMR tutorials
Show steps
Supplement your learning by following guided tutorials from AWS on EMR. This will provide you with additional practical examples and insights.
Browse courses on
AWS EMR
Show steps
-
Go through the AWS EMR documentation
-
Follow step-by-step tutorials on EMR cluster creation and management
Review key concepts of Hadoop
Show steps
Reviewing core Hadoop concepts will improve your foundational understanding and enable you to better grasp subsequent course material.
Browse courses on
Big Data Technologies
Show steps
-
Read through Hadoop tutorials and documentation
-
Practice using Hadoop commands through online tutorials or exercises
Brush up on Hadoop basics
Show steps
Refresh your knowledge of Hadoop concepts like the Hadoop Distributed File System (HDFS), MapReduce, and YARN to prepare for this course.
Browse courses on
Hadoop
Show steps
-
Review Apache Hadoop documentation
-
Go through online tutorials on MapReduce and HDFS
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice MapReduce jobs
Show steps
Get hands-on experience with MapReduce by writing and running your own jobs. This will solidify your understanding of MapReduce concepts.
Browse courses on
MapReduce
Show steps
-
Set up a Hadoop development environment
-
Write a simple MapReduce program
-
Run your MapReduce program on a dataset
Attend an AWS EMR workshop
Show steps
Enroll in an AWS EMR workshop conducted by experts to gain hands-on experience and interact with professionals in the field.
Browse courses on
AWS EMR
Show steps
-
Research and find a relevant AWS EMR workshop
-
Register for the workshop and attend
Follow Amazon EMR tutorials
Show steps
Amazon EMR tutorials can help you familiarize yourself with its features and enhance your understanding of the course material.
Browse courses on
EMR
Show steps
-
Choose a tutorial relevant to your skill level
-
Follow the tutorial steps carefully
-
Experiment with different configurations and settings
Create a simple EMR cluster
Show steps
Hands-on experience in creating an EMR cluster will reinforce your understanding of the process and allow you to apply your knowledge practically.
Show steps
-
Set up the necessary AWS account and permissions
-
Configure the EMR cluster with appropriate settings
-
Launch the cluster and monitor its progress
Build a data pipeline with EMR
Show steps
Create a data pipeline using EMR to gain practical experience in data processing and management. This will help you apply the concepts learned in this course.
Browse courses on
Data Pipelines
Show steps
-
Design the data pipeline architecture
-
Configure and launch EMR clusters
-
Ingest data into HDFS
-
Process data using MapReduce jobs
-
Store the processed data in a database or data warehouse
Help fellow learners with EMR concepts
Show steps
Offer support to other learners by answering their questions on AWS EMR forums or discussion groups. This will reinforce your understanding and help solidify your knowledge.
Browse courses on
AWS EMR
Show steps
-
Join AWS EMR community forums
-
Actively participate in discussions and help others
Follow AWS EMR tutorials
Show steps
Supplement your learning by following guided tutorials from AWS on EMR. This will provide you with additional practical examples and insights.
Browse courses on
AWS EMR
Show steps
Show steps
Show steps
- Go through the AWS EMR documentation
- Follow step-by-step tutorials on EMR cluster creation and management
Review key concepts of Hadoop
Show steps
Reviewing core Hadoop concepts will improve your foundational understanding and enable you to better grasp subsequent course material.
Browse courses on
Big Data Technologies
Show steps
Show steps
Show steps
- Read through Hadoop tutorials and documentation
- Practice using Hadoop commands through online tutorials or exercises
Brush up on Hadoop basics
Show steps
Refresh your knowledge of Hadoop concepts like the Hadoop Distributed File System (HDFS), MapReduce, and YARN to prepare for this course.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Review Apache Hadoop documentation
- Go through online tutorials on MapReduce and HDFS
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice MapReduce jobs
Show steps
Get hands-on experience with MapReduce by writing and running your own jobs. This will solidify your understanding of MapReduce concepts.
Browse courses on
MapReduce
Show steps
Show steps
Show steps
- Set up a Hadoop development environment
- Write a simple MapReduce program
- Run your MapReduce program on a dataset
Attend an AWS EMR workshop
Show steps
Enroll in an AWS EMR workshop conducted by experts to gain hands-on experience and interact with professionals in the field.
Browse courses on
AWS EMR
Show steps
Show steps
Show steps
- Research and find a relevant AWS EMR workshop
- Register for the workshop and attend
Follow Amazon EMR tutorials
Show steps
Amazon EMR tutorials can help you familiarize yourself with its features and enhance your understanding of the course material.
Browse courses on
EMR
Show steps
Show steps
Show steps
- Choose a tutorial relevant to your skill level
- Follow the tutorial steps carefully
- Experiment with different configurations and settings
Create a simple EMR cluster
Show steps
Hands-on experience in creating an EMR cluster will reinforce your understanding of the process and allow you to apply your knowledge practically.
Show steps
Show steps
Show steps
- Set up the necessary AWS account and permissions
- Configure the EMR cluster with appropriate settings
- Launch the cluster and monitor its progress
Build a data pipeline with EMR
Show steps
Create a data pipeline using EMR to gain practical experience in data processing and management. This will help you apply the concepts learned in this course.
Browse courses on
Data Pipelines
Show steps
Show steps
Show steps
- Design the data pipeline architecture
- Configure and launch EMR clusters
- Ingest data into HDFS
- Process data using MapReduce jobs
- Store the processed data in a database or data warehouse
Help fellow learners with EMR concepts
Show steps
Offer support to other learners by answering their questions on AWS EMR forums or discussion groups. This will reinforce your understanding and help solidify your knowledge.
Browse courses on
AWS EMR
Show steps
Show steps
Show steps
- Join AWS EMR community forums
- Actively participate in discussions and help others
Career center
Learners who complete Introduction to Amazon Elastic MapReduce (EMR) will develop knowledge and skills
that may be useful to these careers:
Big Data Architect
Big Data Architect
A Big Data Architect designs and builds big data systems and solutions. This course, Introduction to Amazon Elastic MapReduce (EMR), can help Big Data Architects build a foundation in using EMR to process and analyze large datasets, a critical skill for designing and managing big data systems.
Data Analyst
Data Analyst
A Data Analyst uses mathematical and statistical techniques to examine and interpret data, turning it into a form that can be easily understood and used by business users. This course, Introduction to Amazon Elastic MapReduce (EMR), can help Data Analysts build a foundation in using EMR to process and analyze large datasets, a valuable skill for working with big data.
Business Analyst
Business Analyst
A Business Analyst uses data and analysis to help businesses make better decisions. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Business Analysts who want to learn how to use EMR to process and analyze large datasets, a common task in data-driven decision making.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Software Engineers who want to learn how to use EMR to process and analyze large datasets, a common task in developing and maintaining big data systems.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases, which are used to store and manage data. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Database Administrators who want to learn how to use EMR to process and analyze large datasets, a common task in managing big data systems.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains the infrastructure and processes that enable data scientists and analysts to access and use data. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Engineers who want to learn how to use EMR to process and analyze large datasets, a common task in big data environments.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and manages cloud computing systems. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Cloud Architects who want to learn how to use EMR to process and analyze large datasets, a common task in designing and managing cloud-based big data systems.
DevOps Engineer
DevOps Engineer
A DevOps Engineer works to bridge the gap between development and operations teams, ensuring that software is developed and deployed efficiently and reliably. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for DevOps Engineers who want to learn how to use EMR to process and analyze large datasets, a common task in managing big data systems.
Data Protection Officer
Data Protection Officer
A Data Protection Officer is responsible for ensuring that an organization complies with data protection laws and regulations. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Protection Officers who want to learn how to use EMR to process and analyze large datasets, a common task in data protection.
Data Warehouse Architect
Data Warehouse Architect
A Data Warehouse Architect designs and builds data warehouses, which are used to store and manage large amounts of data. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Warehouse Architects who want to learn how to use EMR to process and analyze large datasets, a common task in managing data warehouses.
Data Governance Analyst
Data Governance Analyst
A Data Governance Analyst develops and implements policies and procedures for managing data, ensuring that it is accurate, consistent, and secure. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Governance Analysts who want to learn how to use EMR to process and analyze large datasets, a common task in managing data governance.
Data Security Analyst
Data Security Analyst
A Data Security Analyst protects data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Security Analysts who want to learn how to use EMR to process and analyze large datasets, a common task in data security.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Scientists who want to learn how to use EMR to process and analyze large datasets, a common task in big data environments.
Data Visualization Analyst
Data Visualization Analyst
A Data Visualization Analyst creates visual representations of data, such as charts and graphs, to help businesses understand their data. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Data Visualization Analysts who want to learn how to use EMR to process and analyze large datasets, a common task in creating data visualizations.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and maintains machine learning models and systems. This course, Introduction to Amazon Elastic MapReduce (EMR), may be useful for Machine Learning Engineers who want to learn how to use EMR to process and analyze large datasets, a common task in training and deploying machine learning models.
For more career information including salaries, visit:
OpenCourser.com/course/3b2074/introduction
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Amazon Elastic MapReduce (EMR).
Provides a comprehensive overview of Hadoop, including its architecture, components, and use cases. It good starting point for understanding the fundamentals of Hadoop.
Save
Provides a concise overview of Hadoop, including its architecture, components, and use cases. It good starting point for understanding the basics of Hadoop.
Save
Provides a practical guide to using Hadoop for data processing. It covers topics such as cluster setup, data ingestion, and data analysis. It good resource for learning how to use Hadoop in a real-world setting.
Provides a beginner-friendly introduction to Hadoop. It covers topics such as Hadoop architecture, data processing, and application development. It good resource for getting started with Hadoop.
Provides a collection of design patterns for developing MapReduce applications. It covers topics such as data partitioning, data sorting, and data aggregation. It good resource for learning how to design and develop efficient MapReduce applications.
Save
Provides a comprehensive guide to Hadoop operations. It covers topics such as cluster management, data security, and performance tuning. It good resource for learning how to operate a Hadoop cluster in a production environment.
Provides a comprehensive guide to Hadoop security. It covers topics such as authentication, authorization, and encryption. It good resource for learning how to secure a Hadoop cluster.
Provides a practical guide to using Hadoop in the enterprise. It covers topics such as data governance, data quality, and data integration. It good resource for learning how to use Hadoop to solve real-world business problems.
Save
Provides a practical guide to using Hadoop for data processing. It covers topics such as cluster setup, data ingestion, and data analysis. It good resource for learning how to use Hadoop in a real-world setting.
Provides a comprehensive guide to using MapReduce for text processing. It covers topics such as data preprocessing, text tokenization, and text classification. It good resource for learning how to use MapReduce to solve real-world text processing problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3b2074/introduction
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