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Jong-Moon Chung
Every time you use Google to search something, every time you use Facebook, Twitter, Instagram or any other SNS (Social Network Service), and every time you buy from a recommended list of products on Amazon.com you are using a big data system. In addition, big data technology supports your smartphone, smartwatch, Alexa, Siri, and automobile (if it is a newer model) every day. The top companies in the world are currently using big data technology, and every company is in need of advanced big data technology support. Simply put, big data technology is not an option for your company, it is a necessity for survival and growth. So now is the right time to learn what big data is and how to use it in advantage of your company. This 6 module course first focuses on the world’s industry market share rankings of big data hardware, software, and professional services, and then covers the world’s top big data product line and service types of the major big data companies. Then the lectures focused on how big data analysis is possible based on the world’s most popular three big data technologies Hadoop, Spark, and Storm. The last part focuses on providing experience on one of the most famous and widely used big data statistical analysis systems in the world, the IBM SPSS Statistics. This course was designed to prepare you to be more successful in businesses strategic planning in the upcoming big data era. Welcome to the amazing Big Data world!
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What's inside
Syllabus
Big Data Rankings & Products
The first module “Big Data Rankings & Products” focuses on the relation and market shares of big data hardware, software, and professional services. This information provides an insight to how future industry, products, services, schools, and government organizations will be influenced by big data technology. To have a deeper view into the world’s top big data products line and service types, the lecture provides an overview on the major big data company, which include IBM, SAP, Oracle, HPE, Splunk, Dell, Teradata, Microsoft, Cisco, and AWS. In order to understand the power of big data technology, the difference of big data analysis compared to traditional data analysis is explained. This is followed by a lecture on the 4 V big challenges of big data technology, which deal with issues in the volume, variety, velocity, and veracity of the massive data. Based on this introduction information, big data technology used in adding global insights on investments, help locate new stores and factories, and run real-time recommendation systems by Wal-Mart, Amazon, and Citibank is introduced.
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Syllabus
Big Data Rankings & Products
The first module “Big Data Rankings & Products” focuses on the relation and market shares of big data hardware, software, and professional services. This information provides an insight to how future industry, products, services, schools, and government organizations will be influenced by big data technology. To have a deeper view into the world’s top big data products line and service types, the lecture provides an overview on the major big data company, which include IBM, SAP, Oracle, HPE, Splunk, Dell, Teradata, Microsoft, Cisco, and AWS. In order to understand the power of big data technology, the difference of big data analysis compared to traditional data analysis is explained. This is followed by a lecture on the 4 V big challenges of big data technology, which deal with issues in the volume, variety, velocity, and veracity of the massive data. Based on this introduction information, big data technology used in adding global insights on investments, help locate new stores and factories, and run real-time recommendation systems by Wal-Mart, Amazon, and Citibank is introduced.
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Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Covers the core concepts and tools used in the big data industry
Emphasizes the practical application of big data technologies, making it relevant for professionals in various industries
Taught by experienced instructors with expertise in big data, ensuring high-quality content
The course is project-based, providing hands-on experience in working with big data tools
Leverages industry-leading technologies such as Hadoop, Spark, and IBM SPSS Statistics
Requires a strong foundation in programming and data analysis concepts
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Reviews summary
Overview of key big data technologies
According to learners, this course provides a solid overview of the big data landscape, covering major technologies like Hadoop, Spark, and Storm with helpful comparisons. Many appreciate the foundational understanding it offers, particularly the insights into market trends and strategic applications. However, a recurring point is the lack of depth and hands-on coding examples, making it less suitable for those seeking technical expertise. The final module on IBM SPSS Statistics is frequently mentioned, with some finding it a useful practical exercise while others consider it outdated and irrelevant compared to open-source alternatives. Overall, it's viewed as a strong introduction for a strategic perspective rather than deep technical skill building.
Opinions mixed on clarity and pace.
"The instructor does a good job explaining the basics of Hadoop and Spark."
"However, the lectures could be dry at times and some concepts felt rushed."
"The Storm module was less clear to me."
Better for strategic overview than deep tech.
"Excellent course for getting a strategic understanding of big data."
"As someone from a business background, this course was perfect."
"If you're looking for hands-on coding and technical skills, this might not be enough."
Divisive module, relevance questioned.
"The final SPSS project felt a bit out of place compared to the other technologies..."
"The SPSS part was interesting but not what I expected after learning about the open-source tools."
"The SPSS module seems irrelevant for anyone planning to work with modern big data stacks based on Hadoop/Spark."
"Inclusion of SPSS feels completely out of touch with the current big data ecosystem..."
Good introduction to core technologies.
"This course gave me a really solid overview of the big data landscape."
"I appreciated the comparisons between Hadoop, Spark, and Storm. It helped me understand where each technology fits."
"It introduces the main players like Spark and Hadoop effectively."
High-level overview, lacks technical depth.
"I wished there was more hands-on coding, especially with Spark, as the focus felt more conceptual than practical."
"The course is too superficial. It skims over important technical details of Spark and Storm."
"There's almost no coding or practical labs, which is essential for learning these technologies."
"Not recommended if you want to build technical skills."
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 Emerging Technologies with these
activities:
Overview of big data systems
Show steps
Review the basic concepts of big data systems to enhance understanding of the course content.
Browse courses on
Big Data
Show steps
-
Read the course overview and syllabus.
-
Watch introductory videos on big data.
-
Complete practice exercises on big data fundamentals.
Study Group Discussions
Show steps
Reinforce your understanding and challenge your perspectives by engaging in discussions with peers.
Show steps
-
Provide feedback and support to your peers.
-
Join an online study group or create your own.
-
Discuss course concepts, assignments, and industry trends.
Spark Exploration
Show steps
Enhance your understanding of Spark and its applications through guided tutorials.
Browse courses on
Spark
Show steps
-
Find online tutorials on Spark basics.
-
Follow along with the tutorials, completing exercises and assignments.
-
Apply what you've learned to analyze sample datasets.
Two other activities
Expand to see all activities and additional details
Show all five activities
Big Data Coding Challenges
Show steps
Strengthen your coding skills in big data technologies through practice drills.
Browse courses on
Spark
Show steps
-
Solve coding problems on platforms like LeetCode or HackerRank.
-
Participate in online coding competitions.
-
Implement big data algorithms and techniques in personal projects.
Real-Time Data Analysis Project
Show steps
Apply your knowledge to a real-world big data project and build confidence.
Browse courses on
Big Data Analytics
Show steps
-
Choose a dataset and define your project goals.
-
Design and implement your data pipeline using Storm or another technology.
-
Analyze your data and draw insights.
-
Present your findings and discuss your approach.
Overview of big data systems
Show steps
Review the basic concepts of big data systems to enhance understanding of the course content.
Browse courses on
Big Data
Show steps
Show steps
Show steps
- Read the course overview and syllabus.
- Watch introductory videos on big data.
- Complete practice exercises on big data fundamentals.
Study Group Discussions
Show steps
Reinforce your understanding and challenge your perspectives by engaging in discussions with peers.
Show steps
Show steps
Show steps
- Provide feedback and support to your peers.
- Join an online study group or create your own.
- Discuss course concepts, assignments, and industry trends.
Spark Exploration
Show steps
Enhance your understanding of Spark and its applications through guided tutorials.
Browse courses on
Spark
Show steps
Show steps
Show steps
- Find online tutorials on Spark basics.
- Follow along with the tutorials, completing exercises and assignments.
- Apply what you've learned to analyze sample datasets.
Two other activities
Expand to see all activities and additional details
Show all five activities
Big Data Coding Challenges
Show steps
Strengthen your coding skills in big data technologies through practice drills.
Browse courses on
Spark
Show steps
Show steps
Show steps
- Solve coding problems on platforms like LeetCode or HackerRank.
- Participate in online coding competitions.
- Implement big data algorithms and techniques in personal projects.
Real-Time Data Analysis Project
Show steps
Apply your knowledge to a real-world big data project and build confidence.
Browse courses on
Big Data Analytics
Show steps
Show steps
Show steps
- Choose a dataset and define your project goals.
- Design and implement your data pipeline using Storm or another technology.
- Analyze your data and draw insights.
- Present your findings and discuss your approach.
Career center
Learners who complete Big Data Emerging Technologies will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use advanced analytics tools to collect, clean, and analyze data to identify patterns and trends. They then use this information to make recommendations and solve business problems. Big Data is a rapidly growing field, and Data Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Data Analyst.
Big Data Architect
Big Data Architect
Big Data Architects design and implement Big Data solutions. They work with businesses to understand their data needs and then design and build systems to meet those needs. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Big Data Architect.
Data Scientist
Data Scientist
Data Scientists use advanced analytics techniques to solve complex business problems. They work with large datasets to identify patterns and trends, and then develop models to predict future outcomes. Big Data is a rapidly growing field, and Data Scientists with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Data Scientist.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models. They work with businesses to understand their business needs and then develop models to solve those needs. Big Data is a rapidly growing field, and Machine Learning Engineers with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Machine Learning Engineer.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. They ensure that databases are running smoothly and that data is safe and secure. Big Data is a rapidly growing field, and Database Administrators with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Database Administrator.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with businesses to understand their needs and then develop software solutions to meet those needs. Big Data is a rapidly growing field, and Software Engineers with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Software Engineer.
Business Analyst
Business Analyst
Business Analysts work with businesses to understand their needs and then develop solutions to meet those needs. They often use data analysis techniques to identify patterns and trends, and then develop recommendations to improve business performance. Big Data is a rapidly growing field, and Business Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Business Analyst.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines. They work with businesses to understand their data needs and then design and build systems to collect, clean, and process data. Big Data is a rapidly growing field, and Data Engineers with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Data Engineer.
Statistician
Statistician
Statisticians use statistical methods to analyze data and draw conclusions. They work with businesses to understand their data needs and then develop statistical models to answer questions and make predictions. Big Data is a rapidly growing field, and Statisticians with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Statistician.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. They work with businesses to understand their needs and then develop models to optimize operations. Big Data is a rapidly growing field, and Operations Research Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become an Operations Research Analyst.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make investment recommendations. They work with businesses to understand their financial needs and then develop models to predict future financial performance. Big Data is a rapidly growing field, and Financial Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Financial Analyst.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. They work with businesses to understand their marketing needs and then develop models to predict customer behavior. Big Data is a rapidly growing field, and Marketing Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Marketing Analyst.
Risk Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. They work with businesses to understand their risk needs and then develop models to predict future risks. Big Data is a rapidly growing field, and Risk Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Risk Analyst.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze data and make investment recommendations. They work with businesses to understand their investment needs and then develop models to predict future investment performance. Big Data is a rapidly growing field, and Quantitative Analysts with skills in Big Data technologies are in high demand. This course provides a comprehensive overview of Big Data technologies and techniques, making it an ideal choice for those who want to become a Quantitative Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/udf8uh/big
Reading list
We've selected ten 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 Emerging Technologies.
Is the definitive reference for Apache Spark, the fast and general-purpose distributed computing engine. It includes topics such as streaming data, machine learning, and graph processing with Spark. If you are interested in Spark, then this must-read.
Save
Focuses on big data architecture and provides the knowledge for you to build big data systems from scratch. Topics covered include real-time data processing with Apache Storm, distributed storage systems such as Apache HDFS, and stream processing systems like Apache Kafka.
Provides a Java-centric view of big data analytics. Topics covered include using Hadoop, Spark, and Storm. You can follow along with the code examples in the book to get hands-on experience with these technologies.
Widely used as a university textbook, this book is considered an advanced exploration of the Hadoop framework. It covers the internals of Hadoop, Hadoop data formats, and the Hadoop ecosystem, making it a great reference for advanced Hadoop knowledge.
Save
While this book little dated, it provides a good foundation for big data and its components. Big data analytics, data science, and big data governance are discussed along with data lakes and data warehouses. Finally, big data security and privacy are discussed.
Save
While this book focuses on R, it provides a great introduction to data science concepts and techniques. Topics covered include data wrangling, data visualization, and statistical modeling. If data science interests you, this great addition to this course with Spark having integration with R.
Provides a business-oriented view of data science. Topics covered include data mining, machine learning, and data visualization. It good choice for someone who is interested in using data science to solve business problems.
Provides a practical introduction to big data technologies. Topics covered include data storage, data processing, and data visualization. It good starting point for someone who is new to big data.
Written with the beginner in mind, this book provides an overview of data analytics. Topics covered include data collection, data cleaning, and data analysis. It good introduction to the field of data analytics.
Provides a comprehensive glossary of big data terms. It valuable resource for anyone who wants to learn more about big data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/udf8uh/big
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Yonsei University
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This course belongs to a
collection
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Emerging Technologies: From Smartphones to IoT to Big Data. It's comprised of four courses:
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