Managing Big Data in Clusters and Cloud Storage from Coursera

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)

What's inside

Syllabus

Orientation to Data in Clusters and Cloud Storage

Defining Databases, Tables, and Columns

Data Types and File Types

Traffic lights

Read about what's good

what should give you pause

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

Reviews summary

Managing big data with hive and impala

According to learners, this course provides a solid foundation in managing big data using Hive and Impala. Students found the lectures clear and the content relevant for building a career in data. The hands-on labs were frequently mentioned as a major strength, offering practical experience. However, some reviewers noted that the virtual machine setup can be challenging and a potential barrier to entry. A few also felt the content could be more in-depth on certain topics or that some parts might be slightly outdated given the rapid pace of technology.

Useful for career development in data roles.

"This course gave me practical skills directly applicable to my job in data engineering."

"Relevant content for anyone looking to work with large datasets on distributed systems."

"Helped me understand the technologies used in many big data environments."

"A valuable addition to my skillset for a career in the big data domain."

Provides a good introduction to core concepts.

"The course provides a good high-level introduction to managing data in Hadoop and cloud storage with Hive/Impala."

"I found the explanations of data types, file formats, and basic Hive/Impala queries to be very clear and concise."

"Good for beginners looking to understand the basics of big data storage and querying on clusters."

"Covers the essential knowledge needed to start working with these technologies."

Excellent hands-on exercises for real skills.

"The hands-on labs were fantastic; really helped solidify the concepts and get practical experience with Hive and Impala."

"I appreciated the practical side of the course. Doing the labs is essential for understanding how to actually use these tools."

"The assignments and hands-on portions were the most beneficial part, letting me apply what I learned directly."

"These practical exercises gave me confidence to use the tools in a real-world setting."

Some content feels slightly behind current practices.

"While the fundamentals are covered, some aspects of the tools and ecosystem have evolved, making parts feel a bit dated."

"Could benefit from updates to reflect the latest versions of the tools and more cloud-native approaches."

"Some information was accurate at the time but might not fully align with current best practices or newer technologies."

"I wish the course covered more recent developments in the big data landscape."

Installing the required virtual machine is difficult.

"Getting the virtual machine set up was a major headache; it took a long time and caused frustration before starting the actual course."

"The biggest challenge for me was getting the VM to work correctly. The instructions could be clearer or troubleshooting help more readily available."

"I almost gave up on the course because of the VM setup. It requires a decent machine and some technical comfort."

"The VM setup process felt overly complex and outdated compared to cloud-based alternatives."

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

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Brush up on your Linux command line skills to navigate and manage big data environments.

Browse courses on Linux

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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

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Refreshing your knowledge of big data will help you better grasp the advanced concepts covered in the course.

Browse courses on Big Data

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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

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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

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Review SQL syntax and commands

24 other activities

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Show all 27 activities

Data Types and File Formats Comparison

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Compile and compare different data types and file formats used in big data systems.

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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

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Revising database fundamentals will strengthen your understanding of the course materials.

Browse courses on Databases

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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

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Familiarize yourself with the powerful tools and services offered by Google Cloud Platform for managing and analyzing big data.

Browse courses on BigQuery

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Follow the Getting Started with BigQuery tutorial
Explore the Google Cloud Platform documentation

Find a Mentor in Big Data

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Having a mentor can provide valuable guidance, support, and insights that can accelerate your learning and growth in big data.

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Identify potential mentors
Reach out to and connect with your chosen mentor

Review SQL Basics

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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

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Read the SQL Tutorial
Complete the SQL Practice Exercises

Attend Apache Hadoop Meetup

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Meet and interact with professionals in the field to gain valuable insights and network.

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Find a local Apache Hadoop Meetup group.
Register and attend the event.
Actively participate in discussions and ask questions.

HiveQL and Impala Practice Exercises

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Enhance your proficiency in HiveQL and Impala querying through regular practice.

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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

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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

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Search for Apache Hive tutorials online
Follow through with the tutorials

Explore Apache Impala Tutorials

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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

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Search for Apache Impala tutorials online
Follow through with the tutorials

Design a Data Loading and Management Plan

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Plan and document your approach to loading and managing big data in a structured manner.

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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

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Completing tutorials will provide practical guidance on loading and storing data for big data analysis.

Browse courses on Data Loading

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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

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Solidify your understanding of data loading and querying techniques by working through hands-on exercises in Apache Hive and Apache Impala.

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Load sample data into a Hive table
Write SQL queries to retrieve data from the table

Practice Writing SQL Queries

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Writing SQL queries is essential for managing and analyzing big data, practice regularly to improve your proficiency.

Browse courses on Apache Hive

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Find online SQL practice exercises
Set aside time for regular practice

Troubleshooting Apache Hive and Impala Queries

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Enhance your problem-solving skills by seeking guidance on troubleshooting Apache Hive and Impala queries.

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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

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Regular practice will enhance your proficiency in writing efficient SQL queries for big data analysis.

Browse courses on SQL

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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

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Gain practical experience by creating a comprehensive data management plan that outlines your data management policies and procedures.

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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

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Join the Apache Hive community and make valuable contributions to the platform.

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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

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Connect with professionals in the big data field, learn about industry trends, and expand your network.

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Locate a local Big Data Meetup or conference
Register and attend the event

Build a Data Pipeline Using Apache Hive and Impala

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To solidify your understanding, attempt to build a data pipeline using both Apache Hive and Apache Impala.

Browse courses on Apache Hive

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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

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Developing a presentation will encourage you to synthesize and communicate your understanding of data optimization techniques.

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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

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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

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Identify a suitable Big Data hackathon
Form a team or join an existing team

Write a Blog Post on Big Data Management

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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

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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

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Building a data pipeline will provide you with hands-on experience in managing and processing real-world big data.

Browse courses on Data Pipeline

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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

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Mentoring others reinforces your knowledge, helps you identify areas for improvement, and contributes to the community.

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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.

See salaries and explore the career path for 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.

See salaries and explore the career path for Big Data Engineer

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.

See salaries and explore the career path for Data Architect

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.

See salaries and explore the career path for Data Scientist

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.

See salaries and explore the career path for Machine Learning Engineer

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.

See salaries and explore the career path for Statistician

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.

See salaries and explore the career path for Database Administrator

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.

See salaries and explore the career path for Business Analyst

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.

See salaries and explore the career path for Data Engineer

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Cloud Architect

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.

See salaries and explore the career path for IT Manager

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.

See salaries and explore the career path for Project Manager

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.

See salaries and explore the career path for Data Warehouse Manager

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.

See salaries and explore the career path for Information Security Analyst