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Introduction to Amazon Elastic MapReduce (EMR)
AWS
AWS
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.
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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.
Read more
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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Activities
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Introduction to Amazon Elastic MapReduce (EMR).
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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.
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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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