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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.

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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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Adding Machine Learning to the Pipeline

Good to know

Know what's good
, what to watch for
, 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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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.
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
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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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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.
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.
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.
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.
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.
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.
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.

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