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Ian Cook and Glynn Durham

In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.

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In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.

By the end of the course, you will be able to

• use different tools to browse existing databases and tables in big data systems;

• use different tools to explore files in distributed big data filesystems and cloud storage;

• create and manage big data databases and tables using Apache Hive and Apache Impala; and

• describe and choose among different data types and file formats for big data systems.

To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements:

• Windows, macOS, or Linux operating system (iPads and Android tablets will not work)

• 64-bit operating system (32-bit operating systems will not work)

• 8 GB RAM or more

• 25GB free disk space or more

• Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled;

on Windows and Linux computers, you might need to enable it in the BIOS)

• For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

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What's inside

Syllabus

Orientation to Data in Clusters and Cloud Storage
Defining Databases, Tables, and Columns
Data Types and File Types
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Managing Datasets in Clusters and Cloud Storage
Optimizing Hive and Impala (Honors)
Honors (Optional)

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines big data tools and technologies, which are core skills for any developer working with large datasets
Taught by Ian Cook and Glynn Durham, who are recognized for their work in big data and data engineering
Develops fundamental big data skills, such as using Apache Hive and Apache Impala, which are crucial for data analysis and management
Emphasizes data management in cloud storage, a highly relevant topic in modern data engineering
Involves the use of hands-on virtual machines, providing practical experience in big data environments

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Reviews summary

Big data clusters and cloud storage: engaging and comprehensive

Learners say this course is an engaging and comprehensive introduction to managing big data in clusters and cloud storage. Reviewers mention they enjoyed the many hands-on exercises and relevant case studies. They also say the course is well-structured and well-paced. Many students found the readings to be helpful and say the instructors are knowledgeable and engaging. Overall, students say this course is a valuable learning experience for anyone interested in big data.
Real-world case studies help students apply their learning.
"I would like to implement the skills that I learnt in this course in some project."
"Amazing course. Both instructors have motivated me to learn more and utilize this platform more than I did ever before."
"I am also very happy they covered Amazon S3."
Course materials are well-organized and easy to follow.
"This is one of the systematic specializations which makes the harder and otherwise overwhelming subject so easy to navigate, follow and learn."
"Great course and specialization. Great instructors and course materials."
"All course structure, and content was well thought out for a online course."
Instructors are knowledgeable, engaging, and provide clear explanations.
"The both lectorers delivered their knowledge."
"The instructors are really good and I learned a lot about Hive, Impala and SQL in general."
"There are very much qualified, they are thorough knowledgable and give good direction on what is important and how it all works."
Practical, hands-on exercises help reinforce learning.
"Super useful course with a lot of hands on practices."
"Very good material and the labs using the VM are wonderful hands-on experience. "
"One of the very few - learn it by doing it - big data courses that deals topics like Hadoop, Hive, Impala comprehensively and unambiguously."
Some reviewers prefer more video content and less reading.
"I prefer the type of course where the class is teached in video. This course have many lectures."
"The course is good designed and information is well structured and explained."
"Compared to the first 2 courses, this course feels somewhat lacking in the video lectures as learners are given more readings to go through."

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 Managing Big Data in Clusters and Cloud Storage with these activities:
Review Linux Command Line Basics
Brush up on your Linux command line skills to navigate and manage big data environments.
Browse courses on Linux
Show steps
  • Take a refresher course or consult documentation.
  • Practice using basic commands in a Linux environment.
  • Review command line options and flags for efficient navigation.
Revisit big data concepts
Refreshing your knowledge of big data will help you better grasp the advanced concepts covered in the course.
Browse courses on Big Data
Show steps
  • Review the characteristics of big data, such as volume, variety, velocity, and veracity.
  • Discuss the different tools and technologies used for big data processing.
  • Explore case studies and examples of big data applications.
Review SQL Syntax
SQL is the main language used to interact with Apache Hive and Apache Impala, refreshing your knowledge will contribute greatly to your engagement in the course.
Browse courses on Apache Hive
Show steps
  • Review SQL syntax and commands
24 other activities
Expand to see all activities and additional details
Show all 27 activities
Data Types and File Formats Comparison
Compile and compare different data types and file formats used in big data systems.
Show steps
  • Research and identify the most common data types and file formats.
  • Create a table or spreadsheet comparing their features and limitations.
  • Include examples of how each data type and file format is used in practice.
Review database concepts
Revising database fundamentals will strengthen your understanding of the course materials.
Browse courses on Databases
Show steps
  • Recall the different types of databases, their advantages, and their disadvantages.
  • Review the concepts of data modeling, including entities, attributes, and relationships.
  • Practice writing SQL queries to retrieve and manipulate data.
Explore BigQuery and Google Cloud Platform
Familiarize yourself with the powerful tools and services offered by Google Cloud Platform for managing and analyzing big data.
Browse courses on BigQuery
Show steps
  • Follow the Getting Started with BigQuery tutorial
  • Explore the Google Cloud Platform documentation
Find a Mentor in Big Data
Having a mentor can provide valuable guidance, support, and insights that can accelerate your learning and growth in big data.
Browse courses on Big Data
Show steps
  • Identify potential mentors
  • Reach out to and connect with your chosen mentor
Review SQL Basics
Warm up with a quick review of essential SQL syntax and fundamentals to strengthen your foundation for working with big data.
Browse courses on SQL
Show steps
  • Read the SQL Tutorial
  • Complete the SQL Practice Exercises
Attend Apache Hadoop Meetup
Meet and interact with professionals in the field to gain valuable insights and network.
Show steps
  • Find a local Apache Hadoop Meetup group.
  • Register and attend the event.
  • Actively participate in discussions and ask questions.
HiveQL and Impala Practice Exercises
Enhance your proficiency in HiveQL and Impala querying through regular practice.
Show steps
  • Find online resources with practice exercises.
  • Set aside dedicated time for practicing queries.
  • Review the documentation and ask questions for clarification.
Explore Apache Hive Tutorials
Apache Hive is a powerful tool for managing big data, use tutorials to familiarize yourself with its features and capabilities.
Browse courses on Apache Hive
Show steps
  • Search for Apache Hive tutorials online
  • Follow through with the tutorials
Explore Apache Impala Tutorials
Apache Impala is a fast and interactive SQL engine for big data, use tutorials to learn how to use it effectively.
Browse courses on Apache Impala
Show steps
  • Search for Apache Impala tutorials online
  • Follow through with the tutorials
Design a Data Loading and Management Plan
Plan and document your approach to loading and managing big data in a structured manner.
Show steps
  • Identify data sources and their formats.
  • Determine the target storage system and its capabilities.
  • Develop a data loading strategy based on performance and cost considerations.
  • Design a data management plan for ongoing maintenance and updates.
Follow tutorials on data loading and storage
Completing tutorials will provide practical guidance on loading and storing data for big data analysis.
Browse courses on Data Loading
Show steps
  • Identify suitable tutorials on data loading and storage.
  • Follow the steps outlined in the tutorials to load and store sample datasets.
  • Experiment with different data types and file formats to understand their impact on storage and performance.
Practice Loading and Querying Data
Solidify your understanding of data loading and querying techniques by working through hands-on exercises in Apache Hive and Apache Impala.
Browse courses on Data Loading
Show steps
  • Load sample data into a Hive table
  • Write SQL queries to retrieve data from the table
Practice Writing SQL Queries
Writing SQL queries is essential for managing and analyzing big data, practice regularly to improve your proficiency.
Browse courses on Apache Hive
Show steps
  • Find online SQL practice exercises
  • Set aside time for regular practice
Troubleshooting Apache Hive and Impala Queries
Enhance your problem-solving skills by seeking guidance on troubleshooting Apache Hive and Impala queries.
Show steps
  • Review documentation and online forums for common errors and solutions.
  • Follow step-by-step tutorials on debugging query issues.
  • Join online communities or ask questions on platforms like Stack Overflow.
Practice writing SQL queries on big data datasets
Regular practice will enhance your proficiency in writing efficient SQL queries for big data analysis.
Browse courses on SQL
Show steps
  • Access sample big data datasets.
  • Write SQL queries to extract, filter, and aggregate data from the datasets.
  • Optimize your queries for better performance.
Develop a Data Management Plan
Gain practical experience by creating a comprehensive data management plan that outlines your data management policies and procedures.
Browse courses on Data Management
Show steps
  • Define the scope and objectives of your data management plan
  • Identify and document data sources and types
  • Develop data storage and security strategies
Contribute to the Apache Hive Community
Join the Apache Hive community and make valuable contributions to the platform.
Show steps
  • Read the Apache Hive documentation and codebase.
  • Identify areas where you can make contributions.
  • Create or join a community project team.
  • Submit bug reports, patches, or documentation updates.
Attend a Big Data Meetup or Conference
Connect with professionals in the big data field, learn about industry trends, and expand your network.
Browse courses on Networking
Show steps
  • Locate a local Big Data Meetup or conference
  • Register and attend the event
Build a Data Pipeline Using Apache Hive and Impala
To solidify your understanding, attempt to build a data pipeline using both Apache Hive and Apache Impala.
Browse courses on Apache Hive
Show steps
  • Design the data pipeline architecture
  • Implement the data pipeline using Apache Hive and Impala
  • Test and validate the data pipeline
Create a presentation on data optimization techniques
Developing a presentation will encourage you to synthesize and communicate your understanding of data optimization techniques.
Browse courses on Data Optimization
Show steps
  • Research and gather information on different data optimization techniques.
  • Organize the information into a logical and visually appealing presentation.
  • Practice delivering the presentation to improve your communication skills.
Participate in a Big Data Hackathon
Put your skills to the test and collaborate with others to develop innovative solutions to real-world big data challenges.
Browse courses on Big Data Challenges
Show steps
  • Identify a suitable Big Data hackathon
  • Form a team or join an existing team
Write a Blog Post on Big Data Management
Writing a blog post on big data management will help solidify your understanding of the concepts, best practices, and tools involved.
Browse courses on Big Data
Show steps
  • Research and gather information on big data management
  • Outline the structure of your blog post
  • Write the content for your blog post
  • Edit and proofread your blog post
  • Publish your blog post
Build a data pipeline for a real-world dataset
Building a data pipeline will provide you with hands-on experience in managing and processing real-world big data.
Browse courses on Data Pipeline
Show steps
  • Identify a suitable real-world dataset.
  • Design and implement a data pipeline to extract, transform, and load the dataset into a storage system.
  • Analyze the data using SQL or other big data tools to extract meaningful insights.
Mentor Junior Students in Big Data
Mentoring others reinforces your knowledge, helps you identify areas for improvement, and contributes to the community.
Browse courses on Big Data
Show steps
  • Offer your services as a mentor
  • Connect with junior students who need guidance
  • Provide support and guidance on big data concepts and tools

Career center

Learners who complete Managing Big Data in Clusters and Cloud Storage will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts are employed to analyze big data with the goal of improving business operations. Their duties include gathering, cleaning, analyzing, and interpreting large datasets. The Cloudera course Managing Big Data in Clusters and Cloud Storage provides the foundation needed to effectively analyze data on a large scale. The skills learned in this course will allow you to perform in the role of a Data Analyst.
Big Data Engineer
Big Data Engineers create and manage the infrastructure, processes, and tools to manage big data. They design, build, test, and maintain the systems that store and process large datasets. This Cloudera course will expose you to the tools and technologies used by Big Data Engineers in the field.
Data Architect
Data Architects design, create, and manage the data management systems used by an organization. They work with business stakeholders to understand data needs and develop data management strategies. This Cloudera course will provide you with a strong foundation in big data management, which is essential for Data Architects.
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. They build models to predict future outcomes and make recommendations. The Cloudera course Managing Big Data in Clusters and Cloud Storage can provide a helpful foundation for a career as a Data Scientist, especially for those interested in working with big data.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work with data scientists to identify and solve business problems using machine learning. While this Cloudera course does not directly teach machine learning, it does provide a strong foundation in data management, which is essential for Machine Learning Engineers.
Statistician
Statisticians collect, analyze, interpret, and present data. They use statistical methods to solve problems in a variety of fields. While this Cloudera course does not directly teach statistics, it does provide a strong foundation in data management, which is essential for Statisticians.
Database Administrator
Database Administrators are responsible for the installation, configuration, maintenance, and performance of database systems. They work with users to understand data needs and develop database solutions. This Cloudera course will help you build a strong foundation in database management, which is essential for Database Administrators, particularly those working with big data.
Business Analyst
Business Analysts use data to identify and solve business problems. They work with stakeholders to gather requirements, analyze data, and develop solutions. This Cloudera course can provide a helpful foundation for a career as a Business Analyst, especially for those interested in working with big data.
Data Engineer
Data Engineers design, build, and maintain the data pipelines that move data between different systems. They work with data scientists and other data professionals to ensure that data is clean, consistent, and accessible. This Cloudera course will help you build a strong foundation in data management, which is essential for Data Engineers, particularly those working with big data.
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with users to understand software needs and develop software solutions. While this Cloudera course does not directly teach software engineering, it does provide a strong foundation in data management, which is increasingly important for Software Engineers working on big data projects.
Cloud Architect
Cloud Architects design, build, and maintain cloud computing systems. They work with customers to understand their business needs and develop cloud solutions. This Cloudera course can provide a helpful foundation for a career as a Cloud Architect, especially for those interested in working with big data.
IT Manager
IT Managers plan, organize, and direct the implementation of information technology systems. They work with users to understand business needs and develop IT solutions. This Cloudera course can provide a helpful foundation for a career as an IT Manager, especially for those interested in working with big data.
Project Manager
Project Managers plan, organize, and execute projects. They work with stakeholders to define project scope, develop project plans, and track project progress. This Cloudera course can provide a helpful foundation for a career as a Project Manager, especially for those working on big data projects.
Data Warehouse Manager
Data Warehouse Managers are responsible for the design, construction, and maintenance of data warehouses. They work with users to understand data needs and develop data warehouse solutions. This Cloudera course will help you build a strong foundation in data management, which is essential for Data Warehouse Managers, particularly those working with big data.
Information Security Analyst
Information Security Analysts plan and implement security measures to protect an organization's information systems. They work with users to identify security risks and develop security solutions. While this Cloudera course does not directly teach information security, it does provide a strong foundation in data management, which is increasingly important for Information Security Analysts working with big data.

Reading list

We've selected eight 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 Managing Big Data in Clusters and Cloud Storage.
Provides a practical guide to designing and building data-intensive applications. Useful for learners interested in the architectural considerations of big data systems.
Provides a comprehensive guide to operating and managing Hadoop clusters. Useful as a reference for learners responsible for deploying and maintaining big data systems.
Provides a practical guide to data science techniques and their application to business problems. Useful for learners interested in using big data for business intelligence.
Provides a practical introduction to data analytics techniques and their application to business problems. Useful for learners with limited background in data analytics.
Provides a comprehensive overview of database systems, including data models, query processing, and transaction management. Useful as background reading or for learners interested in the underlying concepts of big data systems.
Provides a high-level overview of big data and its impact on businesses and society. Useful as background reading or for learners interested in the broader context of big data.
Provides an overview of cloud computing principles and technologies. Useful as background reading or for learners interested in the deployment of big data systems in the cloud.

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