May 2, 2024
3 minute read
Dimensional Modeling is a technique used in data warehousing to organize and present data in a way that makes it easy to analyze and understand. It is a powerful tool that can help businesses improve their decision-making and gain a competitive advantage.
What is Dimensional Modeling?
Dimensional Modeling is based on the concept of dimensions and facts. Dimensions are the different perspectives from which data can be viewed, such as time, location, and product. Facts are the measurements or observations that are associated with dimensions.
For example, a sales database might have the following dimensions:
And the following facts:
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Find a path to becoming a Dimensional Modeling. Learn more at:
OpenCourser.com/topic/f0o3d2/dimensional
Reading list
We've selected 27 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
Dimensional Modeling.
This set includes the three core Kimball Toolkit books, offering a comprehensive library of his foundational work on dimensional modeling, the data warehouse lifecycle, and ETL. Owning this set provides access to the most authoritative guides in the field and must-have for serious practitioners. These are considered classics and must-reads.
Focusing specifically on the Extract, Transform, Load (ETL) process, this book provides essential techniques for populating a dimensional data warehouse. It's a critical companion to the primary Toolkit book for anyone involved in the data integration aspects of dimensional modeling. useful reference for ETL developers.
A recent publication focusing on building analytical data models using SQL and dbt, a popular tool in modern data stacks. is highly relevant for understanding contemporary practices in creating and managing dimensional-like models in cloud-based data warehouses. It dives into contemporary topics and tools.
Introduces an agile approach to dimensional modeling, emphasizing collaboration with business stakeholders. It provides practical techniques for gathering requirements and iteratively developing dimensional models. Relevant for contemporary data warehousing practices that prioritize flexibility and speed.
Offers a collection of data warehouse designs for various business areas, providing practical examples of how dimensional modeling can be applied to solve real-world business problems. It's a useful reference for seeing dimensional modeling in action across different industries and scenarios.
Presents the Unified Star Schema, a hybrid approach combining aspects of Inmon's atomic data warehouse and Kimball's dimensional modeling. It offers a perspective on creating flexible and scalable data warehouse designs in contemporary environments. It is relevant for exploring contemporary topics and deepening understanding of design patterns.
Authored by the 'Father of the Data Warehouse,' this book presents the Corporate Information Factory architecture, a different approach compared to Kimball's dimensional modeling. Reading this provides a broader understanding of data warehousing concepts and alternative designs, offering valuable context for architectural decisions. It is considered a classic in the field.
This guidebook covers the end-to-end process of delivering business intelligence solutions, from data integration to analytics. It helps connect the dots between dimensional modeling and its ultimate purpose of enabling effective business analysis and decision-making. It provides a broader business context for dimensional modeling.
This handbook emphasizes the importance of involving business stakeholders in the data modeling process. It focuses on creating high-level data models that align with business requirements, a crucial aspect of successful dimensional modeling projects. It provides valuable context for the business側 of data modeling.
Explores both relational and dimensional design techniques for data warehouses. It provides a balanced view of the two approaches and helps readers understand when to apply each. It can help deepen understanding by comparing and contrasting different design philosophies.
Provides a deep understanding of the fundamental concepts behind data systems, including storage, processing, and distributed systems. While not directly about dimensional modeling, the knowledge gained is highly valuable for anyone designing and implementing data warehouses and data pipelines that feed them. It provides essential background knowledge for advanced practitioners.
Presents Data Vault modeling, an alternative to dimensional modeling, particularly relevant in agile and big data environments. Understanding Data Vault provides a deeper understanding of data warehousing options and contemporary approaches beyond traditional dimensional modeling. It adds breadth by exploring a different modeling paradigm.
Provides a collection of universal data models that can serve as a starting point for designing dimensional models in various business areas. It offers pre-built structures for common business processes, which can save time and provide guidance during the design phase. It useful reference tool.
Delves into the theoretical underpinnings and practical aspects of data modeling. It explores different modeling approaches and the thinking behind effective data models. While not exclusively dimensional modeling, it provides a deeper understanding of modeling principles that are applicable. It can help deepen understanding of the 'why' behind modeling choices.
While not strictly about dimensional modeling, this book covers essential data management topics like data governance and master data management, which are critical for the success of any data warehousing initiative utilizing dimensional models. It provides important context for implementing dimensional models effectively at scale.
Provides a comprehensive overview of dimensional modeling techniques for building high-performance data warehouses. It is written by W.H. Inmon, Claudia Imhoff, and Zachary Lidsky, three leading experts in data warehousing, and is considered a valuable resource for practitioners.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/f0o3d2/dimensional
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