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Nicholas DeGiacomo,
Shrinath Parikh,
Rostislav Rabotnik,
Vijaya Nelavelli,
Shankar Korrapolu,
and
Ben Larson
Join our big data online training course to gain expertise in designing big data solutions. Learn to identify big data problems and design effective solutions.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- ETL
- Relational database basics
- Command line interface basics
- Basic computer programming
- Basic SQL
Read more
Join our big data online training course to gain expertise in designing big data solutions. Learn to identify big data problems and design effective solutions.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- ETL
- Relational database basics
- Command line interface basics
- Basic computer programming
- Basic SQL
Read more
Join our big data online training course to gain expertise in designing big data solutions. Learn to identify big data problems and design effective solutions.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- ETL
- Relational database basics
- Command line interface basics
- Basic computer programming
- Basic SQL
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/xi4k5o/big
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What's inside
Syllabus
In this lesson, we will take a 30000 foot view of Big Data and see why it is so important. We will meet the instructor and hear about the components of the course, including the final project.
Read more
Syllabus
In this lesson, we will take a 30000 foot view of Big Data and see why it is so important. We will meet the instructor and hear about the components of the course, including the final project.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Explores big data's 4Vs, which is standard in industry
Taught by multiple professionals with experience in the field
Develops skills for designing big data solutions, which is highly relevant to industry
Advises learners to have prior knowledge in ETL, relational database basics, command line interface basics, basic computer programming, and basic SQL, which is a common expectation
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Reviews summary
Big data systems: conceptual foundations and architecture
According to students, this course provides a solid conceptual foundation in Big Data Systems, making it an excellent starting point for understanding the broader ecosystem. Many appreciate its focus on high-level architectural design and the clarity of the instructor's explanations. While effective for grasping the 'why' behind Big Data, some learners note it is heavily theoretical, with a perceived lack of hands-on coding exercises. The final project on Data Lake architecture is frequently highlighted as a valuable capstone, though some wished for more practical application. It is particularly well-suited for professionals seeking a strategic overview rather than deep technical implementation.
Instructor provides clear and concise explanations.
"The instructor was clear and concise."
"The instructor explains things clearly..."
"The explanation of 4Vs and ecosystem was very clear."
Project helps solidify theoretical understanding.
"The final project helped tie things together."
"The final project on Data Lake architecture was a great way to consolidate knowledge."
"It pushed me to think about practical design considerations."
"It encourages critical thinking about system design."
Highly suitable for those new to Big Data or management.
"As someone new to the field, this was a solid start."
"It suited my management role perfectly."
"A good introduction to Big Data for professionals... for managers or architects."
"I recommend this course for anyone who wants to get a high-level understanding of big data systems."
Offers a high-level understanding of Big Data concepts.
"Great conceptual overview of the Big Data ecosystem. The 4Vs and different layers were explained well."
"I found the NoSQL vs SQL comparison very enlightening. The course provides a good high-level understanding."
"This course helped me connect the dots between various Big Data components. The big picture view is what I needed."
"I learned about the different components of a big data system. It was helpful to understand the architectural side."
May be too basic for experienced data professionals.
"Too basic. As someone who works in data engineering, this was mostly review."
"If you have some prior knowledge, it might feel a bit slow."
"It's not for experienced professionals looking to deepen their skills. More for managers or new entrants."
Too theoretical, with insufficient hands-on experience.
"The course provides a decent overview, but I expected more depth on specific tools. It's very conceptual."
"The instructor explains things clearly, but the course lacks practical exercises. It's heavy on theory."
"The syllabus promises 'designing big data solutions' but it's more about understanding concepts behind design. The practical 'how-to' wasn't really there."
"I left with more questions than answers on how to actually implement anything. Needs more practical content."
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 Big Data Systems with these
activities:
Review basic programming concepts
Show steps
Basic programming concepts are essential for working with Big Data. This activity will help students to refresh their skills and ensure that they are ready for the course.
Browse courses on
Programming Fundamentals
Show steps
-
Review online tutorials or documentation
-
Practice writing simple programs
Join a study group or online forum to discuss Big Data
Show steps
Joining a learning community can provide students with support and motivation. It can also help them to learn from others and share their own knowledge.
Browse courses on
Online Learning
Show steps
-
Find a study group or online forum
-
Participate in discussions
-
Help others
Review basics of relational database management
Show steps
Solidify your foundation in the core concepts of relational databases to ensure a strong starting point for this course.
Browse courses on
Relational Databases
Show steps
-
Revisit your notes or textbooks on relational database basics
-
Complete a few practice exercises on database normalization
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Read the Big Data textbook
Show steps
This book provides an excellent overview of the concepts and technologies covered in the course. It will help students to build a foundation needed to succeed in the course.
View
Big Data: Principles and best practices of...
on Amazon
Show steps
-
Read Chapter 1: Introduction to Big Data
-
Read Chapter 2: The 4Vs of Big Data
-
Read Chapter 3: Data Storage and Processing
Explore a guide on Hadoop distributed file system
Show steps
Expand your understanding of a key component of Big Data processing by following a comprehensive guide on Hadoop's distributed file system.
Browse courses on
Hadoop
Show steps
-
Find a tutorial on the Apache Hadoop website
-
Work through the tutorial, completing all exercises
-
Summarize the main concepts you have learned
Follow an online tutorial on NoSQL databases
Show steps
NoSQL is a critical technology for processing large amounts of data. This tutorial will help students gain hands-on experience with a NoSQL database.
Browse courses on
NoSQL
Show steps
-
Follow the tutorial on MongoDB
-
Practice creating and querying a database
Create a data visualization using a tool like Tableau or Power BI
Show steps
Data visualization is a valuable skill for exploring and communicating large datasets. This activity will give students the opportunity to apply their knowledge of big data to a practical task.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset to visualize
-
Learn how to use a data visualization tool
-
Create a visualization that communicates the insights from the data
-
Share your visualization with others
Write a blog post or article on a Big Data topic
Show steps
Writing about a Big Data topic will help students to solidify their understanding of the concepts. It will also give them an opportunity to share their knowledge with others.
Browse courses on
Big Data
Show steps
-
Choose a Big Data topic to write about
-
Research the topic thoroughly
-
Write a blog post or article that is informative and engaging
-
Publish your blog post or article online
Compile your notes, assignments, and quizzes from the course
Show steps
Keeping your materials organized will help you to study more effectively. This activity will help you to compile your materials and prepare for exams.
Show steps
-
Gather your notes, assignments, and quizzes
-
Organize your materials using a filing system or software
-
Review your materials regularly
Start a project to build a Big Data solution
Show steps
Building a Big Data solution will give students the opportunity to apply their knowledge and skills to a real-world problem. It will also help them to develop their creativity and problem-solving abilities.
Browse courses on
Data Science Projects
Show steps
-
Identify a problem or opportunity that can be solved with a Big Data solution
-
Design and develop a solution
-
Implement the solution
-
Evaluate the results
-
Share your solution with others
Review basic programming concepts
Show steps
Basic programming concepts are essential for working with Big Data. This activity will help students to refresh their skills and ensure that they are ready for the course.
Browse courses on
Programming Fundamentals
Show steps
Show steps
Show steps
- Review online tutorials or documentation
- Practice writing simple programs
Join a study group or online forum to discuss Big Data
Show steps
Joining a learning community can provide students with support and motivation. It can also help them to learn from others and share their own knowledge.
Browse courses on
Online Learning
Show steps
Show steps
Show steps
- Find a study group or online forum
- Participate in discussions
- Help others
Review basics of relational database management
Show steps
Solidify your foundation in the core concepts of relational databases to ensure a strong starting point for this course.
Browse courses on
Relational Databases
Show steps
Show steps
Show steps
- Revisit your notes or textbooks on relational database basics
- Complete a few practice exercises on database normalization
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Read the Big Data textbook
Show steps
This book provides an excellent overview of the concepts and technologies covered in the course. It will help students to build a foundation needed to succeed in the course.
View
Big Data: Principles and best practices of...
on Amazon
Show steps
Show steps
Show steps
- Read Chapter 1: Introduction to Big Data
- Read Chapter 2: The 4Vs of Big Data
- Read Chapter 3: Data Storage and Processing
Explore a guide on Hadoop distributed file system
Show steps
Expand your understanding of a key component of Big Data processing by following a comprehensive guide on Hadoop's distributed file system.
Browse courses on
Hadoop
Show steps
Show steps
Show steps
- Find a tutorial on the Apache Hadoop website
- Work through the tutorial, completing all exercises
- Summarize the main concepts you have learned
Follow an online tutorial on NoSQL databases
Show steps
NoSQL is a critical technology for processing large amounts of data. This tutorial will help students gain hands-on experience with a NoSQL database.
Browse courses on
NoSQL
Show steps
Show steps
Show steps
- Follow the tutorial on MongoDB
- Practice creating and querying a database
Create a data visualization using a tool like Tableau or Power BI
Show steps
Data visualization is a valuable skill for exploring and communicating large datasets. This activity will give students the opportunity to apply their knowledge of big data to a practical task.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset to visualize
- Learn how to use a data visualization tool
- Create a visualization that communicates the insights from the data
- Share your visualization with others
Write a blog post or article on a Big Data topic
Show steps
Writing about a Big Data topic will help students to solidify their understanding of the concepts. It will also give them an opportunity to share their knowledge with others.
Browse courses on
Big Data
Show steps
Show steps
Show steps
- Choose a Big Data topic to write about
- Research the topic thoroughly
- Write a blog post or article that is informative and engaging
- Publish your blog post or article online
Compile your notes, assignments, and quizzes from the course
Show steps
Keeping your materials organized will help you to study more effectively. This activity will help you to compile your materials and prepare for exams.
Show steps
Show steps
Show steps
- Gather your notes, assignments, and quizzes
- Organize your materials using a filing system or software
- Review your materials regularly
Start a project to build a Big Data solution
Show steps
Building a Big Data solution will give students the opportunity to apply their knowledge and skills to a real-world problem. It will also help them to develop their creativity and problem-solving abilities.
Browse courses on
Data Science Projects
Show steps
Show steps
Show steps
- Identify a problem or opportunity that can be solved with a Big Data solution
- Design and develop a solution
- Implement the solution
- Evaluate the results
- Share your solution with others
Career center
Learners who complete Big Data Systems will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers help build and maintain systems to store and manage large amounts of data. This course will help Data Engineers understand the different technologies used in Big Data systems, and how to design and implement them. The course will also cover the challenges of working with Big Data, such as data security and scalability.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. This course will help Data Scientists understand the different types of Big Data, and how to use them to build predictive models and make informed decisions. The course will also cover the challenges of working with Big Data, such as data cleaning and feature engineering.
Data Analyst
Data Analyst
Data Analysts use data to identify trends and patterns. This course will help Data Analysts understand the different types of Big Data, and how to use them to perform data analysis. The course will also cover the challenges of working with Big Data, such as data quality and data visualization.
Database Administrator
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course will help Database Administrators understand the different types of Big Data databases, and how to design and implement them. The course will also cover the challenges of working with Big Data, such as data backup and recovery.
Software Engineer
Software Engineer
Software Engineers design and develop software applications. This course will help Software Engineers understand the different types of Big Data technologies, and how to use them to build scalable and efficient applications. The course will also cover the challenges of working with Big Data, such as data integration and data security.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. This course will help Cloud Architects understand the different types of Big Data cloud services, and how to use them to build scalable and cost-effective solutions. The course will also cover the challenges of working with Big Data in the cloud, such as data security and compliance.
Data Architect
Data Architect
Data Architects design and implement data management solutions. This course will help Data Architects understand the different types of Big Data technologies, and how to use them to build scalable and efficient data management solutions. The course will also cover the challenges of working with Big Data, such as data governance and data quality.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. This course will help Machine Learning Engineers understand the different types of Big Data, and how to use them to build accurate and scalable machine learning models. The course will also cover the challenges of working with Big Data, such as data preprocessing and feature engineering.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make better decisions. This course will help Business Analysts understand the different types of Big Data, and how to use them to identify trends and patterns in business data. The course will also cover the challenges of working with Big Data, such as data collection and data analysis.
Project Manager
Project Manager
Project Managers plan and execute projects. This course may be useful for Project Managers who are responsible for managing Big Data projects. The course will help Project Managers understand the different types of Big Data technologies, and how to use them to plan and execute successful Big Data projects.
Data Governance Officer
Data Governance Officer
Data Governance Officers are responsible for managing and protecting data assets. This course may be useful for Data Governance Officers who are responsible for managing Big Data assets. The course will help Data Governance Officers understand the different types of Big Data technologies, and how to use them to implement effective data governance practices.
Information Security Analyst
Information Security Analyst
Information Security Analysts are responsible for protecting information systems from threats. This course may be useful for Information Security Analysts who are responsible for protecting Big Data systems. The course will help Information Security Analysts understand the different types of Big Data technologies, and how to use them to implement effective information security measures.
Compliance Officer
Compliance Officer
Compliance Officers are responsible for ensuring that organizations comply with laws and regulations. This course may be useful for Compliance Officers who are responsible for ensuring that organizations comply with laws and regulations related to Big Data. The course will help Compliance Officers understand the different types of Big Data technologies, and how to use them to implement effective compliance programs.
Risk Manager
Risk Manager
Risk Managers are responsible for identifying and managing risks. This course may be useful for Risk Managers who are responsible for managing risks related to Big Data. The course will help Risk Managers understand the different types of Big Data technologies, and how to use them to identify and manage risks effectively.
Chief Data Officer
Chief Data Officer
Chief Data Officers are responsible for overseeing the use of data within an organization. This course may be useful for Chief Data Officers who are responsible for overseeing the use of Big Data within their organizations. The course will help Chief Data Officers understand the different types of Big Data technologies, and how to use them to drive business value.
For more career information including salaries, visit:
OpenCourser.com/course/xi4k5o/big
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
Big Data Systems.
Provides a practical introduction to MapReduce, a programming model for processing large datasets. It valuable resource for understanding the underlying technologies used in big data processing.
Save
Provides a concise overview of NoSQL databases. It valuable resource for anyone looking to learn more about the different types of NoSQL databases and their applications.
Comprehensive guide to Spark. It covers a wide range of topics, including Spark architecture, data processing, and machine learning.
Save
Provides a comprehensive overview of big data analytics, from strategic planning to enterprise integration. It covers a wide range of topics, including data management, data analysis, and data visualization.
Comprehensive guide to Hadoop, the open-source framework for big data processing. It provides a detailed overview of Hadoop's architecture and components, as well as practical guidance on using Hadoop for data analysis and processing.
Provides a practical guide to data science. It covers a wide range of topics, including data mining, data analysis, and machine learning.
Provides a gentle introduction to machine learning. It valuable resource for anyone looking to learn more about the basics of machine learning.
Provides a comprehensive guide to advanced analytics with Spark. It covers a wide range of topics, including data mining, machine learning, and graph analytics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/xi4k5o/big
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Effort
4 weeks
Level
Advanced
Via
Udacity
Instructors
Nicholas DeGiacomo
Shrinath Parikh
Rostislav Rabotnik
Vijaya Nelavelli
Shankar Korrapolu
Ben Larson
Language
English
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