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Data Warehousing and Business Intelligence

Tim Carrington

This course builds on “The Nature of Data and Relational Database Design” to extend the process of capturing and manipulating data through data warehousing and data mining. Once the transactional data is processed through ETL (Extract, Transform, Load), it is then stored in a data warehouse for use in managerial decision making. Data mining is one of the key enablers in the process of converting data stored in a data warehouse into actionable insight for better and faster decision making.

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This course builds on “The Nature of Data and Relational Database Design” to extend the process of capturing and manipulating data through data warehousing and data mining. Once the transactional data is processed through ETL (Extract, Transform, Load), it is then stored in a data warehouse for use in managerial decision making. Data mining is one of the key enablers in the process of converting data stored in a data warehouse into actionable insight for better and faster decision making.

By the end of this course, students will be able to explain data warehousing and how it is used for business intelligence, explain different data warehousing architectures and multidimensional data modeling, and develop predictive data mining models, including classification and estimation models. IN addition, students will be able to develop explanatory data mining models, including clustering and association models.

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What's inside

Syllabus

Overview of Data Warehousing
Welcome to Module 1, Overview of Data Warehousing. In this module, we will overview data warehousing and data warehousing architectures. We will also define the Extract, Transform, Load (ETL) process as well as touch on data warehousing in the cloud and practice these through a short quiz. Finally, in our activity we will differentiate between the Kimball and Inmon design approaches for data warehouse architecture.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Helps students get ahead in their managerial roles by preparing them for data-driven decision-making
Provides hands-on experience through ETL (Extract, Transform, Load) and data mining processes
Offers a comprehensive overview of data warehousing architectures, including Kimball and Inmon design approaches
Covers data mining methods, including classification, estimation, clustering, and association models
Taught by Tim Carrington, an experienced data warehousing and data mining expert
Requires prior knowledge of data management concepts and SQL

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Reviews summary

Foundational data warehousing & bi concepts

According to learners, this course offers a largely positive experience, particularly excelling in providing a strong theoretical foundation in data warehousing and business intelligence. Many appreciate the clear explanations and well-structured content, which effectively cover core concepts like ETL, multidimensional modeling, and data mining methods. However, a recurring point for improvement is the limited hands-on application. Students often desire more practical labs and real-world case studies to solidify their understanding and prepare them for direct professional application. It is widely considered a great starting point for foundational knowledge.
Ideal for foundational knowledge, potentially too introductory.
"The content is good for a basic overview, but it really stays at a high level. For someone with some experience, it feels a bit too introductory."
"A perfect starting point for understanding data warehousing and business intelligence."
"Decent course for an introduction, but it definitely needs more practical labs or projects."
"I was hoping for more depth in specific data mining algorithms or advanced ETL techniques."
Instructor's explanations are praised for clarity and engagement.
"The instructor's explanations were clear, and the quizzes helped reinforce learning."
"The instructor was engaging. Highly recommend for anyone in BI."
"The instructor simplifies complex ideas beautifully."
"The instructor is knowledgeable."
Provides a clear and comprehensive theoretical understanding.
"This course provided a great introduction to data warehousing concepts and ETL processes."
"Excellent course! The structure is logical, and the material flows well... This course built a strong base for me."
"A perfect starting point for understanding data warehousing and business intelligence. I grasped the core principles without being overwhelmed."
"I appreciated the comprehensive overview of data warehousing and BI. The course nicely explains complex topics."
Reviewers desire more practical labs and real-world projects.
"I wish there were more practical, hands-on labs with real tools."
"I found the lack of practical exercises with actual data sets and software to be a major drawback."
"While the theory is there, the course felt very dry. There were no real-world case studies or opportunities to apply what I learned."
"My main critique is the limited hands-on component; I learn best by doing, and this course was more about understanding concepts."

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 Data Warehousing and Business Intelligence with these activities:
Organize course notes and assignments
Organizing course notes and assignments will help you stay on top of the material and prepare for assessments
Show steps
  • Gather all course materials
  • Create a system for organizing the materials
  • Regularly review the organized materials
Read 'Data Warehousing Fundamentals' by Lawrence Corr
This book provides a comprehensive overview of data warehousing concepts and will complement the course material effectively
View Agile Data Warehouse Design: Collaborative... on Amazon
Show steps
  • Acquire a copy of the book
  • Set aside time for reading
  • Take notes and highlight important concepts
Read chapters on DWH architecture
Reviewing chapters on DWH architecture will help reinforce the concepts covered in our Overview of Data Warehousing Module
Browse courses on Data Warehousing
Show steps
  • Gather the necessary reading materials
  • Set aside a specific time for reading
  • Take notes and highlight key points
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group
Participating in a study group will provide opportunities to discuss course material, ask questions, and learn from peers
Show steps
  • Find or create a study group
  • Set regular meeting times
  • Prepare for each meeting by reviewing the material
  • Actively participate in discussions
Complete data mining exercises
Completing data mining exercises will help reinforce the concepts covered in our Data Mining for Clustering and Association module
Browse courses on Data Mining
Show steps
  • Gather a set of data mining exercises
  • Set aside time to work on the exercises
  • Review the solutions and identify areas for improvement
Learn about data mining methods
Following guided tutorials on data mining methods will help deepen the understanding gained in our Data Mining for Prediction and Explanation module
Show steps
  • Identify reputable sources for tutorials
  • Set aside time to follow the tutorials
  • Take notes and practice the techniques
Create a data warehouse design document
Creating a data warehouse design document will help solidify the concepts covered in our Multidimensional Modeling for Data Warehousing module
Browse courses on Data Warehousing
Show steps
  • Gather the requirements for the data warehouse
  • Design the data warehouse schema
  • Develop a data loading plan
  • Document the design decisions
Participate in a data mining competition
Participating in a data mining competition will provide practical experience and challenge you to apply the concepts covered in this course
Browse courses on Data Mining
Show steps
  • Find a suitable data mining competition
  • Gather a team or work individually
  • Develop a data mining solution
  • Submit your solution and track your progress

Career center

Learners who complete Data Warehousing and Business Intelligence will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst combines their knowledge of data analysis tools and techniques with a business understanding to help organizations make data-driven decisions. Those who want to lead in this position can gain a strong foundation in managing large datasets with data warehousing through this course.
See salaries and explore the career path for Data Analyst
Business Intelligence Analyst
Similar to a Data Analyst, a Business Intelligence Analyst collects and analyzes data to understand business trends and patterns. Data Warehousing and Business Intelligence teaches the fundamental concepts of data mining, modeling, and data warehousing that lend themselves to this role.
See salaries and explore the career path for Business Intelligence Analyst
Data Scientist
Data Scientists use advanced analytical techniques to extract meaningful insights from data. Their skills overlap with the data mining techniques taught in this course, including clustering, association, estimation, and classification models.
See salaries and explore the career path for Data Scientist
Data Engineer
A Data Engineer designs, builds, and maintains data management systems. The course will cover foundational knowledge of data warehousing and multidimensional modeling, which are essential for designing and managing large-scale data systems.
See salaries and explore the career path for Data Engineer
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course will help build a strong foundation for managing data, including data warehousing and multidimensional modeling techniques.
See salaries and explore the career path for Database Administrator
Business Analyst
A Business Analyst helps organizations understand their business processes and make data-driven decisions. This course will provide a foundation in data warehousing and business intelligence, which are essential for understanding data in a business context.
See salaries and explore the career path for Business Analyst
Market Research Analyst
A Market Research Analyst collects and analyzes data to understand market trends and consumer behavior. This course can help build a strong foundation in data mining techniques, which are essential for understanding data and making informed decisions.
See salaries and explore the career path for Market Research Analyst
Marketing Analyst
A Marketing Analyst uses data to understand marketing campaigns and measure their effectiveness. This course teaches data mining techniques that are valuable for understanding data and making informed decisions related to marketing.
See salaries and explore the career path for Marketing Analyst
Financial Analyst
A Financial Analyst uses data to make investment recommendations. Data warehousing and business intelligence concepts are essential for understanding and making sense of financial data.
See salaries and explore the career path for Financial Analyst
Risk Analyst
A Risk Analyst uses data to assess and mitigate risk. Data warehousing and business intelligence concepts are essential for understanding and making sense of risk-related data.
See salaries and explore the career path for Risk Analyst
Operations Research Analyst
An Operations Research Analyst uses data to improve the efficiency of operations. Data warehousing and business intelligence concepts are essential for understanding and making sense of operational data.
See salaries and explore the career path for Operations Research Analyst
Management Consultant
A Management Consultant advises organizations on how to improve their performance. Data warehousing and business intelligence concepts are essential for understanding an organization's data and making informed recommendations.
See salaries and explore the career path for Management Consultant
Data Architect
A Data Architect designs and builds data management systems. This course helps build a strong foundation in data warehousing and modeling, which are essential for designing and managing data systems.
See salaries and explore the career path for Data Architect
Software Engineer
A Software Engineer designs, develops, and maintains software systems. Data warehousing and business intelligence concepts are essential for designing and building software systems that handle data.
See salaries and explore the career path for Software Engineer
Statistician
A Statistician collects, analyzes, and interprets data. This course may be helpful for building a foundation in data mining, which is a specialized field within statistics.
See salaries and explore the career path for Statistician

Reading list

We've selected 12 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 Data Warehousing and Business Intelligence.
Cover image
Spark: The Definitive Guide
Save
Is the definitive guide to Spark, the open-source framework for big data processing. It is an essential resource for anyone who wants to learn more about Spark and how to use it to manage and process big data.
Spark: The Definitive Guide
Paperback
Check
Spark: The Definitive Guide
Kindle Edition
Check
Cover image
Reinforcement Learning, second edition
Save
Classic in the field of reinforcement learning, providing a comprehensive overview of the concepts and algorithms. It is an excellent resource for those who want to learn more about reinforcement learning and its applications in artificial intelligence.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
The Data Warehouse Toolkit
Save
Classic in the field of data warehousing and is widely regarded as one of the most authoritative guides to dimensional modeling. It is an essential read for anyone who wants to design and implement a successful data warehouse.
The Data Warehouse Toolkit
Paperback
Check
The Data Warehouse Toolkit
Kindle Edition
Check
Cover image
Hadoop: The Definitive Guide
Save
Is the definitive guide to Hadoop, the open-source framework for big data processing. It is an essential resource for anyone who wants to learn more about Hadoop and how to use it to manage and process big data.
Hadoop: The Definitive Guide: Storage and Analysis...
Paperback
$$
Hadoop: The Definitive Guide
Kindle Edition
$$
Hadoop: The Definitive Guide
Paperback
$$
Hadoop: The Definitive Guide
Paperback
$$
Cover image
Computer Vision
Save
Provides a comprehensive overview of computer vision, covering all the major concepts and algorithms. It is an excellent resource for those who want to learn more about computer vision and its applications in areas such as image recognition, object detection, and video analysis.
Computer Vision
Paperback
Check
Computer Vision
Kindle Edition
Check
Cover image
The Kimball Group Reader
Save
Provides a comprehensive overview of business intelligence, covering all the major concepts and technologies. It is an excellent resource for those who want to learn more about the role of business intelligence in decision making.
The Kimball Group Reader
Paperback
Check
The Kimball Group Reader
Kindle Edition
Check
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive overview of natural language processing, with a focus on using the Natural Language Toolkit (NLTK) library in Python. It is an excellent resource for those who want to learn more about natural language processing and how to use it to analyze text data.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
(中文) Python Natural Language Processing(Chinese Edition)
Paperback
$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Data Mining
Save
Comprehensive textbook on data mining, covering all the major concepts and techniques. It is an excellent resource for those who want to learn more about data mining and its applications in business intelligence.
Data Mining: Concepts and Techniques (The Morgan...
Kindle Edition
$$$
Data Mining: Concepts and Techniques (The Morgan...
Hardcover
$$$
Data Mining: Concepts and Techniques, Second...
Hardcover
$$
Data Mining: Know It All
Hardcover
$$$
Cover image
Data Visualization
Save
Provides a practical guide to data visualization, focusing on how to create effective and informative visualizations. It valuable resource for those who want to learn more about how to use data visualization to communicate insights.
Data Visualization: A Successful Design Process: A...
Paperback
$
Data Visualization: Representing Information on...
Kindle Edition
$$$
Data Visualization Design and Utilization (Korean...
Paperback
$$$
Cover image
The AI Playbook
Save
Provides a practical guide to predictive analytics, focusing on how to use data to make better decisions. It valuable resource for those who want to learn more about the potential of predictive analytics in business.
The AI Playbook: Mastering the Rare Art of Machine...
Hardcover
$$
The AI Playbook: Mastering the Rare Art of Machine...
Kindle Edition
$$
Cover image
Data Warehousing Fundamentals for IT Professionals
Save
Provides a comprehensive overview of data warehousing, including its concepts, architectures, and methodologies. It is an excellent resource for those who are new to the field or want to refresh their understanding of the fundamentals.
Data Warehousing Fundamentals for IT Professionals
Hardcover
$$$
Data Warehousing Fundamentals: A Comprehensive...
Hardcover
$$
Data Warehousing Fundamentals for IT Professionals
Kindle Edition
$$$$
Cover image
Data Driven Business Transformation
Save
Provides a gentle introduction to machine learning, with a focus on its applications in business. It good choice for those who want to learn about machine learning without getting bogged down in the technical details.
Data Driven Business Transformation: How to Disrupt...
Hardcover
$$
Data Driven Business Transformation: How to Disrupt...
Kindle Edition
$$

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Course image
Effort
4 weeks of study, 1-3 hours/week
Level
Introductory
Via
Coursera
Institution
University of California, Irvine
Instructor
Tim Carrington
Language
English
This course belongs to a collection called Database Design and Operational Business Intelligence. It's comprised of three courses:
  1. The Nature of Data and Relational Database Design
  2. Business Intelligence and Visual Analytics
  3. Data Warehousing and Business Intelligence (viewing)
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Helps students get ahead in their managerial roles by preparing them for data-driven decision-making
Provides hands-on experience through ETL (Extract, Transform, Load) and data mining processes
Offers a comprehensive overview of data warehousing architectures, including Kimball and Inmon design approaches
Covers data mining methods, including classification, estimation, clustering, and association models
Taught by Tim Carrington, an experienced data warehousing and data mining expert
Requires prior knowledge of data management concepts and SQL
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