May 1, 2024
Updated June 30, 2025
20 minute read
Measures are a fundamental concept in data analysis and reporting. They provide a concise way to summarize and quantify data, making it easier to understand and communicate insights. Measures can be used for a variety of purposes, including tracking key performance indicators (KPIs), comparing different data sets, and identifying trends.
Why Learn About Measures?
There are many reasons why you might want to learn about measures. Perhaps you're a student or researcher who needs to analyze data for a project. Or maybe you're a business professional who wants to use data to make better decisions. Whatever your reasons, learning about measures can help you to:
- Gain a deeper understanding of data
- Make better use of data for decision-making
- Communicate insights more effectively
- Advance your career
If you're interested in learning more about measures, there are a number of online courses that can help you get started. These courses cover a variety of topics, including:
- The basics of measures
- How to create and use measures in different software programs
- Advanced techniques for data analysis and reporting
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Find a path to becoming a Measures. Learn more at:
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Reading list
We've selected 35 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
Measures.
Is considered a foundational text in the field of data warehousing and dimensional modeling, which is crucial for understanding how measures and dimensions are structured and utilized in business intelligence. It provides a comprehensive guide to designing effective data models that support analytical queries. While some technical details might be dated, the core principles remain highly relevant and are essential background knowledge for anyone working with measures in a BI context. It is widely used as a reference and textbook in academic and professional settings.
Following the success of 'The Definitive Guide to DAX', this book provides practical, reusable solutions to common business problems using DAX. It presents a collection of patterns that demonstrate how to apply DAX concepts to real-world scenarios, which is extremely useful for understanding how to effectively define and use measures. is more valuable as a reference and source of advanced techniques after gaining a foundational understanding of DAX. It's a highly recommended resource for professionals looking to deepen their DAX knowledge and apply it to complex problems.
For professionals working with large datasets and complex models, optimizing the performance of measures written in DAX is essential. delves into advanced techniques for optimizing DAX expressions, helping users write more efficient and scalable measures. This resource for experienced DAX users looking to fine-tune their calculations and improve query performance.
Offers a comprehensive overview of measures used in business intelligence and data mining, discussing their types, applications, and advantages.
Provides a comprehensive guide to modern business intelligence, including a detailed discussion of measures used to analyze business data.
Provides a comprehensive treatment of causal inference methods, including the use of measures to assess the strength and directionality of causal effects.
Great reference for the implementation of measures. It bit more advanced and focuses on the algorithmic side of computation.
Focuses on the practical implementation of measuring using SQL and Excel. It great way to apply the learnt theoretical knowledge.
Provides a practical guide to using Power BI and Power Pivot for data analysis, with a strong focus on applying DAX to create measures and reports. It offers hands-on examples and case studies that demonstrate how to build data models and perform calculations using measures. This book is particularly useful for those learning to work with measures within the context of these specific tools and serves as a good bridge between theoretical DAX knowledge and practical application. It can be used as a textbook for learning data analysis with Power BI.
Focuses specifically on data modeling within Power BI, which is directly relevant to defining and organizing measures and dimensions for optimal performance and usability. It covers advanced modeling techniques and best practices for building robust and efficient data models in Power BI. This valuable resource for professionals working extensively with Power BI who want to deepen their understanding of how modeling impacts measure creation and report performance.
Understanding data modeling is fundamental to defining effective measures and dimensions. provides a practical and accessible introduction to data modeling concepts, focusing on the techniques needed to create effective models for business needs. It is particularly helpful for those new to data modeling and provides a solid foundation for understanding how data structures impact the creation and use of measures. It good starting point before diving into more complex data warehousing topics.
Aims to help Power BI users understand the underlying concepts of DAX to write more effective measures. It focuses on building a strong foundation in DAX thinking, which is essential for creating accurate and insightful measures in Power BI. This good resource for those who have started using DAX but need to improve their understanding of how it works to write more complex measures.
Presents an agile approach to dimensional modeling, emphasizing collaboration and iterative development. It provides practical techniques for designing dimensional models that effectively support business requirements and the creation of measures. This valuable resource for data modelers and BI teams looking to adopt a more agile methodology for their data warehousing projects.
Provides a comprehensive guide to using Microsoft Power BI, covering various aspects of the platform, including data modeling and the use of measures. It helps users understand how to leverage the full capabilities of Power BI to build interactive reports and dashboards that effectively utilize defined measures. This valuable resource for anyone working extensively with Power BI.
Provides a solid foundation in statistics for data analysis, covering various measures of central tendency, dispersion, and association.
Offers a broad overview of the entire business intelligence lifecycle, providing context for where measures and dimensions fit within a larger BI strategy. It covers topics from data integration to analytics, helping readers understand the process of transforming raw data into actionable insights. This good resource for gaining a broad understanding of the landscape in which measures are used and is valuable for both students and professionals seeking a holistic view of BI. It can serve as a useful reference for understanding the various components of a BI system.
Provides a collection of universal data models that can serve as a starting point for designing databases and data warehouses. Understanding these common data model patterns is helpful for correctly defining dimensions and measures within a structured framework. It's a valuable reference for data modelers and those involved in the design phase of data solutions.
Is great to start a journey in data analytics from scratch. It gives a broad overview of measures and their importance.
Provides a detailed roadmap for the entire business intelligence project lifecycle, from planning to deployment and maintenance. Understanding this lifecycle helps in understanding where the definition and implementation of measures fit within a larger project context. It's a valuable resource for project managers and BI professionals involved in the end-to-end delivery of BI solutions.
Specifically aimed at Power BI users, this book introduces the DAX language with a focus on creating measures within the Power BI environment. It provides a beginner-friendly guide to understanding the basics of DAX and how it's used to add calculations and intelligence to Power BI models. This practical starting point for those learning Power BI and needing to create basic measures.
Discusses the importance of interpretable measures in machine learning models, providing techniques for developing and evaluating models that are both accurate and understandable.
Focuses on econometric methods for analyzing cross-sectional and panel data, covering various measures used to assess model fit and data characteristics.
Offers an accessible introduction to machine learning, covering the use of measures for model evaluation and optimization.
Introduces the fundamental principles of data science and data-analytic thinking, which provides a broader context for the application of measures in extracting value from data. It covers various data mining techniques and how they relate to business problems, helping readers understand how measures contribute to analytical insights. This good resource for understanding the strategic importance of data and measures in a business context.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/4p9skl/measure
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