18 Business Intelligence Books You Can’t Miss
From theory to application, a well-chosen book can elevate your business intelligence acumen and open doors to profitability you hadn't imagined. If you're looking to learn about the latest BI strategies and technologies, you're in the right place.
Overview Of 18 Best Business Intelligence Books
Having navigated numerous BI titles, I've chosen the best to address the most pressing challenges in SaaS today.
- Competing on Analytics by Thomas H. Davenport and Jeanne G. Harris
- Data Science for Business by Foster Provost and Tom Fawcett
- Predictive Analytics by Eric Siegel
- Data Warehousing For Dummies by Thomas C. Hammergren
- Business Intelligence Guidebook by Rick Sherman
- Data Warehousing Toolkit by Ralph Kimball
- Big Data at Work by Thomas H. Davenport
- Business Intelligence Roadmap by Larissa T. Moss and Shaku Atre
- Performance Dashboards by Wayne W. Eckerson
- Data Management for Researchers by Kristin Briney
- Too Big to Ignore by Phil Simon
- Secrets of Analytical Leaders by Wayne Eckerson
- The Signal and the Noise: Why So Many Predictions Fail — but Some Don't by Nate Silver.
- QlikView Your Business by Oleg Troyansky, Tammy Gibson, and Charlie Leichtweis
- Superforecasting by Philip E. Tetlock and Dan M. Gardner
- The Data Warehouse Toolkit by Ralph Kimball and Margy Ross
- Information Dashboard Design by Stephen Few.
- Learn Power BI: A Comprehensive, Step-by-Step Guide for Beginners to Learn Real-World Business Intelligence by Greg Deckler
Overview Of 18 Best Business Intelligence Books
1. Competing on Analytics by Thomas H. Davenport and Jeanne G. Harris
Summary:
In "Competing on Analytics," Davenport and Harris articulate how data-driven strategies and analytics, much like what you'd find in "business intelligence for dummies" or works by Cindi Howson, can furnish companies with a distinct competitive edge in today's business world. They weave a narrative around the transformative influence of analytics, even delving into data analysis tools such as Excel. Their insights spotlight the pivotal role analytics plays across diverse sectors, highlighting the essence of successful business intelligence.
What You'll Learn:
Within its pages, readers will unravel the fundamental concepts of business analytics, discover how top-tier companies employ analytics in guiding their decision-making processes, and glean techniques to entrench analytics deep within an organization's DNA.
Why You Should Read It:
This book stands as a beacon for those aiming to grasp the core tenets of analytics and leverage them as a strategic tool in the contemporary, cutthroat business milieu.
About The Author:
Thomas H. Davenport holds the accolade of Distinguished Professor at Babson College and is also a research fellow with the MIT Initiative on the Digital Economy. Jeanne G. Harris is an esteemed executive research fellow and a pivotal figure at Accenture's Institute for High Performance.
2. Data Science for Business by Foster Provost and Tom Fawcett
Summary:
Provost and Fawcett craft a compelling narrative in "Data Science for Business," integrating themes of big data analytics, data-analytic thinking, and the burgeoning influence of the internet of things. As the digital landscape evolves with platforms like Amazon leading the charge and the proliferation of apps tapping into vast data reservoirs, they offer readers an exhaustive primer on data science paradigms and their implications in the commercial domain. The authors have a knack for simplifying these intricate subjects, rendering them palatable to business aficionados sans a technical pedigree.
What You'll Learn:
The book dives deep into the salient principles of data science, elucidating their intersection with cogent business strategies. It also sheds light on methodologies that pry valuable insights from sprawling datasets, all the while peppering the discourse with tangible applications and illustrative case studies, manifesting data science in tangible form.
Why You Should Read It:
It serves as an invaluable bridge linking the theoretical realm of data science to its tangible, real-world business ramifications, priming readers to harness data insights in steering their decision-making compass.
About The Author:
Foster Provost occupies the esteemed chair of Professor of Data Science and Information Systems at NYU Stern School of Business. In tandem, Tom Fawcett boasts an illustrious career spanning over a quarter of a century in the domain, punctuated with seminal academic contributions in data mining and machine learning.
3. Predictive Analytics by Eric Siegel
Summary:
In "Predictive Analytics," Siegel embarks on an exploratory odyssey, demystifying the vast expanse of predictive analytics. Drawing inspiration from top business analytics books, he elucidates how a robust BI strategy and business intelligence strategy can address real business problems. By emphasizing the prediction of human comportment, Siegel showcases how these insights can profoundly sculpt the trajectory of businesses, proving invaluable for business managers eager to harness data-driven solutions.
What You'll Learn:
Readers are ushered into the foundational universe of predictive analytics, gaining insights into how organizations channelize predictive revelations to catalyze growth. Siegel doesn't shy away from delving into the ethical quandaries and the broader societal reverberations that stem from predictive decision-making.
Why You Should Read It:
Siegel's opus offers a panoramic view of predictive analytics, spanning its mathematical roots to its overarching influence on contemporary business ethos and practices.
About The Author:
Eric Siegel, a former luminary in the halls of Columbia University's Computer Science department, stands at the forefront of the predictive analytics sphere. His visionary zeal also birthed the acclaimed Predictive Analytics World conference series. You can also find him on his LinkedIn.
4. Data Warehousing For Dummies by Thomas C. Hammergren
Summary:
"Data Warehousing For Dummies" serves as a compass for those navigating the intricate terrains of data warehousing in a world where understanding how to profit from a world of big data is crucial. Hammergren masterfully distills the essence of data warehousing, emphasizing the data strategy that can unlock immense business value. By understanding the core principles, businesses can carve a competitive advantage, truly appreciating the value of BI & big data. This makes the subject not only approachable for beginners but also refreshing and insightful for the well-acquainted.
What You'll Learn:
The narrative explores the foundational pillars of data warehousing, elucidating its architecture, design principles, and integration techniques. The book also sheds light on leveraging data warehouses for business insights, weaving together the technical and strategic facets of the discipline.
Why You Should Read It:
For anyone keen on getting a solid grounding in data warehousing or desiring a refresher, this book offers a balanced blend of theory and practical insights, making the world of data warehousing both accessible and engaging.
About The Author:
Thomas C. Hammergren is an industry veteran with vast experience in business intelligence, data warehousing, and data governance. His insights are shaped by years of hands-on work and thought leadership in the field.
5. Business Intelligence Guidebook by Rick Sherman
Summary:
Sherman's "Business Intelligence Guidebook," often considered the ultimate guide, is a meticulous exploration into the universe of business intelligence (BI) and realms like artificial intelligence and SQL. Building upon the success of his acclaimed "big data demystified" in the first edition, the second edition offers readers the tools to master data analysis. The author delves deep, presenting a holistic perspective that encompasses both the granular technicalities and overarching strategies of BI.
What You'll Learn:
Readers are introduced to the multifaceted world of BI—from understanding its architectural foundations to appreciating its role in decision-making processes. Sherman also discusses the challenges that organizations face in BI implementation and provides guidance on building robust BI infrastructures.
Why You Should Read It:
This guide stands out as a comprehensive resource for both BI novices and seasoned practitioners. With its balanced approach, readers will find themselves equipped to navigate the BI landscape with confidence.
About The Author:
Rick Sherman is a renowned BI consultant and founder of Athena IT Solutions. His rich experience and deep understanding of the domain have made him a sought-after speaker and educator in the world of business intelligence. You can also find him on his LinkedIn.
6. Data Warehousing Toolkit by Ralph Kimball
Summary:
In "Data Warehousing Toolkit," Kimball crafts a masterful treatise on the methodologies and best practices integral to the world of data warehousing. With his distinct clarity and depth, he offers readers a journey that is both enlightening and actionable.
What You'll Learn:
The book unveils the myriad facets of data warehousing, encompassing topics such as dimensional modeling, ETL processes, and data warehouse design. Kimball's insights pave the way for effective data warehouse implementations, fostering a culture of data-driven decision-making.
Why You Should Read It:
As a seminal work in its field, this book is a must-read for those aspiring to harness the power of data warehousing in their organizations. Kimball's expertise ensures a blend of foundational knowledge and advanced techniques, catering to a broad spectrum of readers.
About The Author:
Ralph Kimball is a luminary in the realm of data warehousing and business intelligence. With a career spanning decades, his contributions have shaped the industry's methodologies and best practices, earning him worldwide recognition and respect.
7. Big Data at Work by Thomas H. Davenport
Summary:
Davenport's "Big Data at Work" offers a compelling insight into the transformative power of big data in the business arena. The book navigates the promises and pitfalls of big data, serving as both a cautionary tale and an illuminating guide for organizations seeking to harness its potential.
What You'll Learn:
Readers will gain a comprehensive understanding of what big data entails, its business implications, and strategies for its successful integration. Davenport discusses the convergence of analytics with big data, offering practical advice on leveraging this union for optimum business impact.
Why You Should Read It:
This tome is invaluable for decision-makers looking to navigate the big data revolution effectively. Davenport’s astute observations ensure that readers are well-equipped to embrace big data's opportunities while sidestepping its challenges.
About The Author:
Thomas H. Davenport, a prolific author and expert in the realm of analytics and big data, holds prestigious positions at Babson College and the MIT Initiative on the Digital Economy. His writings have significantly influenced business strategies globally.
8. Business Intelligence Roadmap by Larissa T. Moss and Shaku Atre
Summary:
Moss and Atre's "Business Intelligence Roadmap" is a comprehensive guide that charts the intricate journey of BI projects. Through detailed insights and real-world examples, the authors provide a blueprint for BI success.
What You'll Learn:
The book covers the lifecycle of BI projects, from initial planning and requirements gathering to deployment and post-implementation reviews. Emphasis is placed on understanding business needs, ensuring data quality, and fostering collaboration across teams.
Why You Should Read It:
For professionals embarking on BI initiatives, this roadmap is indispensable. Moss and Atre's expertise ensures that readers are equipped with the knowledge and tools necessary to steer BI projects to success.
About The Author:
Larissa T. Moss is a pioneer in data warehousing and business intelligence methodologies, with extensive consulting experience. Shaku Atre, an industry stalwart, is known for her expertise in data management and BI, and her ability to bridge the gap between business and technology.
9. Performance Dashboards by Wayne W. Eckerson
Summary:
"Performance Dashboards" by Eckerson is a deep dive into the world of dashboards, visualizations, and performance management. Through a mix of theory and practice, Eckerson elucidates the art and science of transforming data into actionable insights.
What You'll Learn:
The narrative encompasses the principles of effective dashboard design, the significance of data visualization, and strategies to drive actions based on dashboard insights. Eckerson also sheds light on the tools and technologies that power modern dashboards.
Why You Should Read It:
For those keen on mastering the realm of dashboards and performance management, Eckerson’s work stands as an authoritative resource. It's a blend of design philosophy and practical wisdom, ensuring readers can craft dashboards that truly drive decision-making.
About The Author:
Wayne W. Eckerson is a leading figure in the business intelligence and data analytics community. With a career spanning over two decades, his writings, research, and consulting have influenced countless organizations and professionals in the field.
10. Data Management for Researchers by Kristin Briney
Summary:
In "Data Management for Researchers," Kristin Briney delves into the intricacies of handling, organizing, and maintaining research data. It's a meticulously crafted guide, tailored for researchers looking to optimize data management practices for better results and efficiency.
What You'll Learn:
The book covers everything from data planning, organization, documentation, to sharing and storage. Briney emphasizes the importance of ethical considerations in data handling and sheds light on the tools and techniques pivotal to efficient data management.
Why You Should Read It:
Any researcher, irrespective of their discipline, stands to benefit from Briney’s insights. It’s an essential read for those aiming to streamline their research processes and ensure the longevity and integrity of their data.
About The Author:
Kristin Briney is a renowned data scientist with a keen focus on research methodologies. Her passion for enhancing the quality and efficiency of research data management has established her as a trusted voice in the academic and research communities.
11. Too Big to Ignore by Phil Simon
Summary:
Phil Simon's "Too Big to Ignore" is an exploration into the vast world of big data, emphasizing its undeniable impact and relevance in the modern era. Through relatable anecdotes and in-depth analysis, Simon paints a vivid picture of the big data landscape.
What You'll Learn:
Simon touches on the evolution of big data, its transformational effects across industries, and its potential to shape future innovations. The book also delves into the challenges posed by big data and offers strategies to harness its potential effectively.
Why You Should Read It:
For those curious about or working with big data, Simon’s narrative is enlightening. It offers a comprehensive view, making big data’s complexities accessible and its opportunities evident.
About The Author:
Phil Simon is a sought-after speaker, consultant, and author specializing in organizational collaboration and technological adaptation. His forward-thinking approach to big data and its implications has made him a thought leader in the domain.
12. Secrets of Analytical Leaders by Wayne Eckerson
Summary:
Eckerson's "Secrets of Analytical Leaders" offers readers a window into the minds of seven top analytical leaders, as they discuss their experiences, insights, and secrets to success in the realm of analytics.
What You'll Learn:
The narrative provides a comprehensive understanding of the strategies these leaders employ, the challenges they’ve overcome, and their visions for the future of analytics. From leadership nuances to technical intricacies, the book captures the essence of leading in an analytical world.
Why You Should Read It:
For anyone aspiring to leadership roles in analytics or seeking to refine their leadership approach, Eckerson’s compilation is both enlightening and inspiring.
About The Author:
Wayne Eckerson, a prominent figure in business intelligence and data analytics, has a rich history of research, writing, and consulting in the field. His keen insights and vast experience make him a trusted authority on analytical leadership.
13. The Signal and the Noise: Why So Many Predictions Fail — but Some Don't by Nate Silver
Summary:
In The Signal and the Noise, Nate Silver delves into the world of predictions, exploring the dynamics between information (the signal) and distraction or irrelevant data (the noise). With a deep dive into various fields, from politics and economics to weather and poker, Silver unravels the complexities of forecasting and why many predictions fail despite the overwhelming data available.
What You'll Learn:
Silver unveils the art and science behind making accurate predictions. He emphasizes the importance of discernment, probabilistic thinking, and the humility to accept uncertainty. Through real-world examples and case studies, readers will grasp the nuances of distinguishing genuine insights from misleading data.
Why You Should Read It:
In an era flooded with data, the ability to sift through the noise and identify the true signal is paramount. Silver's analysis is both enlightening and practical, offering readers a toolkit to navigate a world rife with predictions and to make informed decisions in their personal and professional lives.
About The Author:
Nate Silver is a statistician, writer, and the founder of FiveThirtyEight, a data-driven news site. He gained international fame for his accurate predictions in the 2008 and 2012 U.S. presidential elections. With a background in economics and a passion for numbers, Silver has established himself as one of the leading voices in data analysis and forecasting.
14. QlikView Your Business by Oleg Troyansky, Tammy Gibson, and Charlie Leichtweis
Summary:
"QlikView Your Business" stands out as an invaluable guide for those diving into the world of QlikView, a leading business intelligence and visualization tool. Troyansky, Gibson, and Leichtweis pull from their vast reservoirs of experience to present a hands-on approach to mastering QlikView.
What You'll Learn:
The book dives deep into QlikView's functionalities, from data modeling and design to advanced scripting and extensions. Readers gain a robust understanding of how to harness QlikView for actionable insights and effective decision-making.
Why You Should Read It:
For professionals working with or considering QlikView, this guide is indispensable. It offers a thorough grounding, ensuring users can make the most of QlikView's capabilities.
About The Author:
Oleg Troyansky is a seasoned QlikView consultant and trainer. Tammy Gibson brings to the table a rich blend of business and technical acumen, while Charlie Leichtweis, with his vast experience, offers strategic insights into BI implementation and management.
15. Superforecasting by Philip E. Tetlock and Dan M. Gardner
Summary:
"Superforecasting" is a riveting exploration into the art and science of prediction. Tetlock and Gardner delve into the world of "superforecasters" – individuals exceptionally adept at predicting future events.
What You'll Learn:
The duo unravel the techniques and mindsets of superforecasters, exploring how they consistently outperform experts in various fields. The narrative covers cognitive biases, probabilistic thinking, and the importance of continuous learning and adaptability in the realm of forecasting.
Why You Should Read It:
For those intrigued by the complexities of prediction or looking to hone their forecasting skills, this book offers invaluable insights, shedding light on the methodologies of the best in the business.
About The Author:
Philip E. Tetlock is a renowned psychologist and professor known for his research on prediction accuracy. Dan M. Gardner is a celebrated journalist and author with a keen interest in the intersections of psychology, history, and public policy.
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16. The Data Warehouse Toolkit by Ralph Kimball and Margy Ross
Summary:
"The Data Warehouse Toolkit" by Kimball and Ross is a comprehensive guide to the world of data warehousing, regarded by many as the definitive source. Drawing upon their extensive expertise, the authors delve into best practices, methodologies, and design techniques pertinent to data warehousing.
What You'll Learn:
Readers will gain an in-depth understanding of dimensional modeling, exploring its nuances and applications. The book provides insights into the lifecycle of data warehousing projects, from conceptualization to implementation, ensuring robust and scalable solutions.
Why You Should Read It:
For professionals in the data warehousing domain or those aspiring to dive into it, this book stands as an authoritative resource, ensuring a solid foundation and advanced mastery.
About The Author:
Ralph Kimball, a luminary in data warehousing, has significantly influenced the industry's methodologies. Margy Ross, co-founder of the Kimball Group, has collaborated extensively with Ralph, co-authoring several definitive works and consulting on numerous high-profile data warehousing projects.
17. Information Dashboard Design by Stephen Few
Summary:
In "Information Dashboard Design," Stephen Few delves into the art of crafting effective and insightful dashboards. Through a blend of design principles and practical examples, Few elucidates how to transform raw data into visual stories that drive decision-making.
What You'll Learn:
The book offers a deep dive into effective dashboard design principles, shedding light on common pitfalls and best practices. Few emphasizes the importance of simplicity, clarity, and integrity in data visualization, guiding readers on creating dashboards that are both informative and intuitive.
Why You Should Read It:
For those engaged in data visualization or keen on mastering dashboard design, Few’s insights are invaluable. The book stands as a beacon for ensuring that dashboards not only look good but also serve their fundamental purpose effectively.
About The Author:
Stephen Few, a recognized expert in data visualization and BI, has dedicated his career to simplifying complex data, making it accessible and actionable for a wide range of audiences. His works are foundational in the field, shaping best practices and influencing generations of data professionals.
18. Learn Power BI: A Comprehensive, Step-by-Step Guide for Beginners to Learn Real-World Business Intelligence by Greg Deckler
Summary:
"Learn Power BI" by Greg Deckler stands as an essential guide for those venturing into the realm of Power BI, Microsoft's powerful business intelligence tool. Deckler meticulously crafts a journey from the basics to more advanced facets, ensuring readers develop a robust understanding tailored for real-world applications.
What You'll Learn:
The narrative covers the vast landscape of Power BI, from data ingestion and transformation to crafting compelling visualizations and reports. Deckler emphasizes hands-on learning, providing readers with practical exercises and examples that resonate with real business scenarios.
Why You Should Read It:
For anyone seeking a firm grasp on Power BI or aiming to harness its capabilities for actionable business insights, Deckler's guide is a treasure trove of knowledge. With its step-by-step approach, even complete beginners will find themselves confidently navigating Power BI’s intricacies.
About The Author:
Greg Deckler is a seasoned expert in business intelligence, with a particular focus on Power BI. His vast experience and knack for simplifying complex concepts make his writings invaluable for both novices and seasoned professionals alike.
Which Business Intelligence Book Do You Recommend?
Of course, the realm of business intelligence is vast and ever-evolving. While we've endeavored to capture some of its seminal works, there might be gems we've overlooked. We invite you to share any notable titles you believe should grace this list. Your insights enrich our collective knowledge!