What are the best books or resources to learn analytical reasoning for business intelligence?

For those diving into the fundamentals of logic for business intelligence, several excellent resources await! "The Data Warehouse Toolkit" by Ralph Kimball and Margy Ross offers practical insights into data modeling and analysis, crucial for BI. "Data Science for Business" by Foster Provost and Tom Fawcett provides a comprehensive overview of data-driven decision-making, while "Python for Data Analysis" by Wes McKinney equips readers with essential Python skills for data manipulation and analysis. For a deeper dive into logic and reasoning, "Introduction to Logic" by Irving M. Copi and Carl Cohen serves as a comprehensive guide. These resources cater to various skill levels and offer a solid foundation for mastering logic in BI contexts.

To build a solid foundation in analytical reasoning for business intelligence, it’s essential to start with the fundamentals of logic. Mastering logical thinking and reasoning is crucial before diving into advanced data analysis. An excellent introductory book is *"Logic: A Complete Introduction"* by Siu-Fan Lee, which offers a comprehensive overview of key concepts like arguments, fallacies, truth tables, syllogisms, and modal logic. This resource will enhance your ability to think clearly and critically, providing a strong base for tackling complex business intelligence challenges.

A crucial aspect of Business Intelligence (BI) is presenting data in a manner that is easy to understand, interpret, and act upon. Data visualization involves the creation of effective charts, graphs, dashboards, and stories that communicate insights clearly. For foundational knowledge, The Visual Display of Quantitative Information by Edward Tufte is a must-read, offering principles and examples of both good and bad visualizations. For a hands-on approach, Data Visualization: A Practical Introduction by Kieran Healy teaches you how to use R and ggplot2 to craft stunning, informative graphics.

The resources mentioned in the article are valuable for learning data analysis and modeling. However, it's important to note that mastering these skills requires a solid foundation in statistical concepts. Moreover, practical application is key; thus, learners should seek opportunities to apply these techniques using real-world data. Lastly, while tools like Excel, Python, R, and SQL are useful, understanding the underlying principles of data analysis is crucial as tools and technologies evolve.

- 📘 "Storytelling with Data" by Cole Nussbaumer Knaflic: Learn principles and practices of effective data storytelling to communicate the meaning and value of data. - 🌐 The Data Story Academy: An online platform offering courses and coaching on data storytelling tailored to various industries and domains. - 📚 "The Big Book of Dashboards" by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave: Provides practical examples of data visualization for different business scenarios. - 📊 "Data Visualization: A Handbook for Data Driven Design" by Andy Kirk: Covers the fundamentals of data visualization and how to create effective visual stories.

My highest recommendation goes to the Tufte series of books. 1. Visual Explanations 2. The Visual Display of Quantitative Information 3. Beautiful Evidence With those three books you have the functional roadmap and guide to building data that any and all of your audience members understand your work. This also opens up the door to the work being passed up and on to executive leadership.

This article section rightly emphasizes the importance of critical thinking in business intelligence. However, it's also worth noting that analytical reasoning goes beyond just critical thinking. It involves a combination of skills including problem-solving, decision-making, and logical reasoning. While the resources mentioned are indeed valuable, one might also consider resources that focus on these other aspects of analytical reasoning. For instance, "Thinking, Fast and Slow" by Daniel Kahneman provides insights into the two systems of thought that drive our decisions, which can be beneficial in BI.

I personally love reading books by builders, i.e Yvon Chouinard's "Let My People Go Surfing" (still one of my favorites), Bob Iger's "Ride of a Lifetime", Jane Fonda "My Life So Far". Critical thinking requires quantitative analysis but also context and creativity. If you can digest a lot of information - great. However, to really excel in critical thinking and business intelligence - I strongly believe that you need to work your creative mind and maybe be inspired by people who've done a lot of critical thinking and problem solving before. Reading stories, analogies of people in a variety of fields helps me to draw parallels and think about the issues I'm facing with some distance, reference, and sometimes even humor. Give it a go.