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Handling and Analyzing Data with AWS Elastic MapReduce

Andru Estes

In this course, you are going to learn how to utilize today's most popular big data tools and ML frameworks to process and analyze data within AWS pipelines.

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In this course, you are going to learn how to utilize today's most popular big data tools and ML frameworks to process and analyze data within AWS pipelines.

A lot of people hear about big data analyzation, but how can you use it for your use cases? In this course, Handling and Analyzing Data with AWS Elastic MapReduce, you’ll learn foundational knowledge and gain the ability to use AWS Elastic MapReduce to perform data analyzation. First, you’ll explore configuring AWS EMR and Hadoop. Next, you’ll discover how to process, move, and query data using big data frameworks. Finally, you’ll learn how to stream and analyze data using Apache products and MLlib. When you’re finished with this course, you’ll have the skills and knowledge of using AWS EMR needed to handle and analyze your own big data datasets.

This course is no longer available. Find something similar by browsing:
AWS Elastic MapReduce Big Data Analytics Hadoop Machine Learning Mllib Apache Products

What's inside

Syllabus

Course Overview
Configuring Elastic MapReduce in a Pipeline
Processing, Moving, and Querying Data
Streaming and Analyzing Data with Apache Products
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Emphasizes the practical application of today's popular big data tools and ML frameworks to process and analyze data within AWS pipelines
Offers comprehensive coverage of AWS Elastic MapReduce, Hadoop, and Apache products, providing a solid foundation for big data analysis
Features practical instruction on Hadoop configuration, data processing, and querying, enabling learners to effectively handle and analyze big data datasets
Provides hands-on experience with industry-standard technologies, ensuring learners are prepared for real-world big data applications
Incorporates streaming and machine learning into the pipeline, enabling learners to explore advanced analytics techniques for big data
Suitable for individuals with a working knowledge of big data concepts and experience with AWS
Taught by expert instructors with extensive experience in big data analysis, ensuring high-quality instruction and practical insights

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Create your own learning path. Save this course to your list so you can find it easily later.
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Reviews summary

Aws emr: foundational data analysis

According to learners, this course is a solid foundation for understanding AWS EMR and big data processing, particularly for beginners. Many praise its clear explanations and practical, hands-on labs and demos that foster practical skill development. However, some learners with prior AWS experience felt the course lacked depth for intermediate topics, particularly for advanced EMR functionalities and optimization. A recurring concern is that parts of the course, especially the AWS console UI, feel outdated, which can make following along difficult. The MLlib section is also frequently noted as too brief. Despite these warnings, it's generally seen as a highly effective starting point for handling and analyzing data in the AWS ecosystem.
Emphasizes hands-on learning with clear examples.
"I found the hands-on labs particularly useful for understanding the practical application."
"The demos were spot on, and I appreciated the step-by-step guidance. It really equipped me with practical skills."
"A very practical course on EMR. I liked the focus on real-world scenarios..."
"The practical approach, with plenty of examples and hands-on exercises, made learning enjoyable and effective."
Excellent for beginners in AWS EMR.
"This course provided a solid foundation in AWS EMR and Hadoop."
"Absolutely fantastic! As someone new to AWS big data, this course was a perfect entry point."
"Excellent coverage of EMR fundamentals... This course is a great starting point, providing a solid theoretical background combined with practical exercises."
"I feel much more confident using EMR now for data processing tasks."
The MLlib content is insufficient.
"My only minor gripe is that some parts felt a bit rushed, especially the MLlib section, which could use more depth."
"The MLlib part was particularly disappointing and felt like an afterthought."
"The MLlib section was too brief."
Course content and AWS UI need updating.
"The course content felt a bit outdated in some areas, especially regarding the AWS console interface, which has changed."
"This made following along frustrating at times. I struggled with some of the labs because the instructions didn't match the current AWS UI."
"My main feedback would be to update the UI screenshots as AWS updates rapidly."
Not suited for intermediate or advanced users.
"While the course covered the basics of EMR, I felt it lacked depth for intermediate users."
"It's good for absolute beginners, but if you have some prior AWS experience, you might find parts too slow or superficial."
"Decent introduction to EMR, but it scratched the surface. I was hoping for more advanced topics..."
"I think it caters more to beginners or those new to EMR rather than experienced data engineers looking for advanced optimization strategies."

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 Handling and Analyzing Data with AWS Elastic MapReduce with these activities:
Read Hadoop The Definitive Guide
Reading this book will provide you with a comprehensive understanding of Hadoop, including its architecture, components, and use cases.
View Hadoop: The Definitive Guide: Storage and... on Amazon
Show steps
  • Read the first chapter of the book.
  • Skim the rest of the book.
  • Go back and read the chapters that are most relevant to your interests.
Follow a Hadoop Tutorial
Following a Hadoop tutorial will allow you to learn the basics of Hadoop and get started with using it.
Show steps
  • Find a Hadoop tutorial that is appropriate for your skill level.
  • Follow the steps in the tutorial.
  • Complete the exercises in the tutorial.
Practice Hadoop Exercises
Practicing Hadoop exercises will help you to reinforce your understanding of the platform.
Show steps
  • Find some Hadoop exercises online.
  • Complete the exercises.
  • Check your answers against the solutions.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a Hadoop Study Group
Joining a Hadoop study group will allow you to connect with other Hadoop users and learn from each other.
Show steps
  • Find a Hadoop study group online or in your local area.
  • Attend the study group meetings.
  • Participate in the discussions.
Contribute to the Hadoop Project
Contributing to the Hadoop project is a great way to learn about Hadoop and get involved in the community.
Show steps
  • Find a Hadoop project to contribute to.
  • Read the project documentation.
  • Make a contribution to the project.
Build a Hadoop Cluster
Building a Hadoop cluster will give you hands-on experience with the platform and help you to understand how it works.
Show steps
  • Gather the necessary hardware.
  • Install the Hadoop software.
  • Configure the Hadoop cluster.
Write a Blog Post about Hadoop
Writing a blog post about Hadoop will help you to solidify your understanding of the platform and share your knowledge with others.
Show steps
  • Choose a topic for your blog post.
  • Write the blog post.
  • Publish the blog post.

Career center

Learners who complete Handling and Analyzing Data with AWS Elastic MapReduce will develop knowledge and skills that may be useful to these careers:
Data Engineer
As a Data Engineer, you would be responsible for designing, implementing, and maintaining big data pipelines within AWS. This course would provide you foundational knowledge and skills in using AWS EMR to process and analyze large datasets. You would gain hands-on experience in configuring AWS EMR and Hadoop, as well as using big data frameworks like Apache Spark and Hive to process, move, and query data. Additionally, you would learn how to stream and analyze data using Apache products like Kafka and Flink, and how to leverage MLlib for machine learning. This course can help you build a strong foundation for a career in Data Engineering.
See salaries and explore the career path for Data Engineer
Data Analyst
As a Data Analyst, you would be responsible for collecting, cleaning, and analyzing data to identify trends, patterns, and insights that can help businesses make better decisions. This course can help you develop the skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, how to use big data frameworks like Apache Spark and Hive to process and analyze data, and how to stream and analyze data using Apache products like Kafka and Flink. Additionally, you would learn how to leverage MLlib for machine learning, which is becoming increasingly important in the field of Data Analytics.
See salaries and explore the career path for Data Analyst
Big Data Architect
As a Big Data Architect, you would be responsible for designing and managing big data solutions for organizations. This course can help you develop the knowledge and skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, how to use big data frameworks like Apache Spark and Hive to process and analyze data, and how to stream and analyze data using Apache products like Kafka and Flink. Additionally, you would learn how to leverage MLlib for machine learning, which is becoming increasingly important in the field of Big Data Architecture.
See salaries and explore the career path for Big Data Architect
Data Scientist
As a Data Scientist, you would be responsible for using data to solve business problems and make predictions. This course can help you develop the skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, how to use big data frameworks like Apache Spark and Hive to process and analyze data, and how to stream and analyze data using Apache products like Kafka and Flink. Additionally, you would learn how to leverage MLlib for machine learning, which is essential for Data Scientists.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
As a Machine Learning Engineer, you would be responsible for developing and deploying machine learning models to solve business problems. This course can help you develop the skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, how to use big data frameworks like Apache Spark and Hive to process and analyze data, and how to stream and analyze data using Apache products like Kafka and Flink. Additionally, you would learn how to leverage MLlib for machine learning, which is essential for Machine Learning Engineers.
See salaries and explore the career path for Machine Learning Engineer
Cloud Engineer
As a Cloud Engineer, you would be responsible for designing, implementing, and managing cloud computing solutions for organizations. This course can help you develop the knowledge and skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, how to use big data frameworks like Apache Spark and Hive to process and analyze data, and how to stream and analyze data using Apache products like Kafka and Flink.
See salaries and explore the career path for Cloud Engineer
Data Integration Engineer
As a Data Integration Engineer, you would be responsible for integrating data from multiple sources into a single, cohesive dataset. This course can help you develop the skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, how to use big data frameworks like Apache Spark and Hive to process and analyze data, and how to stream and analyze data using Apache products like Kafka and Flink.
See salaries and explore the career path for Data Integration Engineer
Database Administrator
As a Database Administrator, you would be responsible for managing and maintaining databases for organizations. This course can help you develop the knowledge and skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Database Administrator
Software Engineer
As a Software Engineer, you would be responsible for designing, developing, and testing software applications. This course can help you develop the knowledge and skills you need to be successful in this role, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Software Engineer
Business Analyst
As a Business Analyst, you would be responsible for analyzing business problems and developing solutions. This course may be useful for you, as it can help you develop the skills you need to understand and analyze data, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Business Analyst
Project Manager
As a Project Manager, you would be responsible for planning, executing, and closing projects. This course may be useful for you, as it can help you develop the skills you need to manage projects that involve big data, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Project Manager
Systems Analyst
As a Systems Analyst, you would be responsible for analyzing business systems and developing solutions. This course may be useful for you, as it can help you develop the skills you need to understand and analyze data, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Systems Analyst
Technical Writer
As a Technical Writer, you would be responsible for writing technical documentation, such as user manuals and whitepapers. This course may be useful for you, as it can help you develop the skills you need to understand and explain complex technical concepts, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Technical Writer
IT Manager
As an IT Manager, you would be responsible for managing an organization's IT systems and infrastructure. This course may be useful for you, as it can help you develop the knowledge and skills you need to manage IT systems that involve big data, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for IT Manager
Data Warehouse Manager
As a Data Warehouse Manager, you would be responsible for managing an organization's data warehouse. This course may be useful for you, as it can help you develop the knowledge and skills you need to manage a data warehouse that involves big data, such as how to configure AWS EMR and Hadoop, and how to use big data frameworks like Apache Spark and Hive to process and analyze data.
See salaries and explore the career path for Data Warehouse Manager

Reading list

We've selected six 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 Handling and Analyzing Data with AWS Elastic MapReduce.
Cover image
Hadoop: The Definitive Guide
Save
Provides an in-depth guide to Apache Hadoop, the open-source framework for distributed processing of large data sets across clusters of computers. It covers the core concepts, architecture, and components of Hadoop, as well as advanced topics such as security, performance tuning, and data science.
Hadoop: The Definitive Guide: Storage and Analysis...
Paperback
$$
Hadoop: The Definitive Guide
Kindle Edition
$$
Hadoop: The Definitive Guide
Paperback
$$
Hadoop: The Definitive Guide
Paperback
$$
Cover image
Learning Spark
Save
Provides a detailed guide to Apache Spark, covering topics such as Spark architecture, programming with Spark, and advanced topics such as streaming data processing and machine learning.
Learning Spark: Lightning-Fast Big Data Analysis
Paperback
$$
Cover image
Hadoop in Practice
Save
Provides a practical guide to Hadoop, covering topics such as Hadoop architecture, data processing, and data analysis. It also provides real-world examples and case studies to help readers apply the concepts learned to their own projects.
Hadoop in Practice: Includes 104 Techniques
Paperback
$$
Hadoop in Practice: Includes 85 Techniques
Paperback
$$
Hadoop in Practice: Includes 104 Techniques
Kindle Edition
$$
Cover image
Big Data Analytics with R and Hadoop
Save
Provides a practical guide to big data analytics using R and Hadoop, covering topics such as data acquisition, data preparation, data analysis, and data visualization. It also provides real-world examples and case studies to help readers apply the concepts learned to their own projects.
Big Data Analytics With R and Hadoop: Set Up an...
Paperback
$$
Cover image
Hadoop For Dummies
Save
Provides a beginner-friendly guide to Hadoop, covering topics such as Hadoop architecture, data processing, and data analysis. It good starting point for those who are new to Hadoop and big data.
Hadoop For Dummies (For Dummies (Computers))
Kindle Edition
$$
Hadoop For Dummies (For Dummies (Computers)) by...
Unknown Binding
$$
[Hadoop For Dummies (For Dummies (Computers))]...
Paperback
$$
Cover image
Spark: The Definitive Guide
Save
Provides a comprehensive guide to Apache Spark Streaming, the extension of Apache Spark for real-time data processing. It covers topics such as Spark Streaming architecture, data ingestion, data processing, and data output.
Spark: The Definitive Guide: Big Data Processing...
Paperback
$$
Spark: The Definitive Guide: Big Data Processing...
Kindle Edition
$$

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Similar courses

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Course image
Time
139 hours
Level
Intermediate
Via
Pluralsight
Instructor
Andru Estes
Language
English
This course belongs to a collection called AWS Big Data. It's comprised of nine courses:
  1. Getting Started with AWS Athena
  2. Implementing Amazon S3 Storage on AWS
  3. Building Your First Amazon Redshift Data Warehouse
  4. Developing Stream Processing Applications with AWS Kinesis
  5. AWS Big Data in Production
  6. Serverless Analytics on AWS
  7. Big Data on AWS: The Big Picture
  8. Handling and Analyzing Data with AWS Elastic MapReduce (viewing)
  9. Building an Elasticsearch Cluster with Amazon Elasticsearch Service on AWS
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Emphasizes the practical application of today's popular big data tools and ML frameworks to process and analyze data within AWS pipelines
Offers comprehensive coverage of AWS Elastic MapReduce, Hadoop, and Apache products, providing a solid foundation for big data analysis
Features practical instruction on Hadoop configuration, data processing, and querying, enabling learners to effectively handle and analyze big data datasets
Provides hands-on experience with industry-standard technologies, ensuring learners are prepared for real-world big data applications
Incorporates streaming and machine learning into the pipeline, enabling learners to explore advanced analytics techniques for big data
Suitable for individuals with a working knowledge of big data concepts and experience with AWS
Taught by expert instructors with extensive experience in big data analysis, ensuring high-quality instruction and practical insights
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