Top 10 Books on Decision Making to Read in 2024 [US}

In today’s information age, the data we generate is a goldmine for businesses. All businesses rely on this readily available and generated user data to shape their business plans and strategies. Globally 2.5 quintillion bytes of data are produced every single day. That is a massive amount of data to sieve through to find relevant and valuable information. Here the genius of data scientists comes in. 

If data are puzzle pieces, then data scientists are puzzle masters. Data science professionals can help navigate organizations through a sea of data and convert them into actionable insights. At their role’s core is optimizing the data gathering and analysis process and leveraging big data to achieve business goals.

Data scientists are at the helm of spearheading a business’s decision-making and problem-solving process. If you want to build a successful career in this field, having a hold over the nuances of decision-making will be an added advantage, which can be made possible with the best books for decision making.

So, you might be wondering how to find the right decision making and problem solving books to ace it. We have you covered. Here is a list of the ten best books for decision making!

Top 10 Books on Decision-Making to Read in 2022

1. Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity by Avinash Kaushik

From the renowned author of Web Analytics: An Hour a Day, this book takes the readers on a journey that transforms them from amateur analysts to data analysis ninjas. In an easily digestible fashion, Kaushik shows you the ropes of web analytics and how to leverage one’s digital presence. Whether debating the best tools to use in web analysis, the metrics of performance to take into account, or how to build a successful career in the field- this book covers it all. For anyone seeking insight into the world of Web Analysis, this book is a gem. 

2. Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic

Gathering and analyzing data is one part of the battle won. The next step involves communicating that data to an audience who are stakeholders in a business’s decision-making process. In this book, Knaflic underscores the importance of storytelling in data analysis. How to declutter data to make it accessible? What visual modes to use to grab the audience’s attention and hold it? What is the importance of context? The author will answer this and numerous other questions you may have on data visualization and its role for business professionals. 

3. Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths

Drawing parallels between computer science with everyday life, this book has a simple message: algorithms are and should be a part of human decision-making. The authors observe that computers and humans typically face similar problems. So, humans, too, can use algorithms in decision-making and problem-solving to increase efficiency and optimize limited resources.

They highlight algorithms that will tell you when to settle, how to optimize your life, predict the future, solve the impossible, and much more. It is a must-read for all data analysts to understand the centrality of algorithms in making decisions and solving problems.

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4. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking by Foster Provost and Tom Fawcett

How can a business stay ahead with data and use it for business advantage? If this is a question you are grappling with, then this book by data science experts should feature in your reading list. This book covers everything from the fundamentals of data science to ways of developing data-analytical thinking.

Beginners and professionals alike can read this book to learn the relevance of data in business decision-making and convert data into actionable insights. Data is the currency of a business, and this book shows you how to leverage it and use several data-mining techniques.

5. The Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page

Businesses are inundated with massive amounts of data regularly. Page, a social scientist, proposes that we use models to make sense of and use this available data. However, instead of opting for a single model, he outlines the significance of the “many-model paradigm” for a more accurate and nuanced understanding- a complete picture. This book should be on the shelves of everyone who want to learn how to organize data using multiple models to increase accuracy and success in their decision-making and problem-solving endeavor. 

6. Superforecasting: The Art and Science of Prediction by Philip E. Tetlock and Dan Gardner

For most people, the ability to predict the future is nothing short of a superpower. In this book, Tetlock and Gardner draw insights from the multi-year study, the Good Judgement Project, to explore what works best for ‘superforecasters’.

Drawing insights from ordinary people to high-level decision-makers, the authors showcase the significance of relying on multiple sources, thinking probabilistically, teamwork, course correction, and much more in predicting the future. This book is a valuable addition for data scientists to develop predictive thinking based on quantification and analysis to augment their decision-making process. 

7. Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman

A book written to be conversational and comfortable, Data Smart is sure to win the hearts of both budding and expert data scientists. Foreman uses humor and spreadsheets to rid the reader of any anxiety they may have over using and analyzing data. He introduces crucial data science techniques and concepts and hand-holds the audience through working with practice problems. The book is almost like having a personal tutor teaching you the A-Z of converting data into usable insight to become “Data Smart.” 

8. The Decision Maker’s Handbook to Data Science by Stylianos Kampakis

According to the tagline, the target audience for this book is non-technical executives, managers, and founders. Kampakis understands the value of introducing data science to non-data scientists at the helm of organizations using or seeking to use data in their operations.

The book simplifies the subject and suggests ways for businesses to gain by using data science, hiring and managing data scientists, demystifying buzzwords, and equipping readers with the tools to develop a data strategy. Add this to the reading list if you are a decision-maker (or just curious) who wants to understand the science of decision-making through data science.

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9. Numsense! Data Science for the Layman: No Math Added by Annalyn Ng and Kenneth Soo

The book’s title says it all: it is data science for the layman. It is a godsend for anyone starting their journey, the curious, or those who want a brief crash course on the subject. The authors aim to gently introduce some key terms and algorithms to beginners using real-world examples and visuals to make the content easy to grasp. This book is a must-read for those who want to tap into the potential of data science in facilitating their decision-making process in language accessible to the layman.

10. Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning by Alex J. Gutman and Jordan Goldmeier

This information-rich book is for anyone who wants to learn about data science from the ground up. The authors cover basic topics to the most complex concepts in a reader-friendly language to communicate and make sense of a data-centric world. It is an essential read providing a guide to navigating the science of data in the workplace.

The authors break down this complex field and its concepts and processes through simple explanations and relatable examples for the readers. This book will help untrained and trained data science professionals in the corporate space streamline decision-making using data. 

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Final Word

Data science has revolutionized how we view and use data. It helps unravel the puzzle to present a complete picture that helps businesses make critical decisions and resolve complex problems. If you want to master the field, read some of the best decision making and problem solving books available.

This list curates the ten best books on decision making in 2022, so you can cut through the noise and get to the heart of leveraging data for competitive business advantage. If you want to further your education in the field, explore upGrad’s course on Data Science and Business Analytics!

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Interact with a highly qualified faculty from one of the most renowned public universities in the US- the University of Maryland- and industry leaders during live lectures and coaching sessions. The course provides a comprehensive curriculum on data science and business analytics. Additionally, the curriculum covers programming languages and tools, such as Python, MySQL, Excel, and Tableau. 

How does Data Science help business?

Data science is at the heart of sieving relevant data from the sea of data available and drawing usable insights for businesses from the patterns that emerge. Data science helps a business make decisions, identify patterns, solve problems, measure performance, increase efficiency and productivity, develop useful products, predict trends and outcomes, improve customer experience and satisfaction, and much more.

What skills should a Data Scientist have?

Essential skills for a data scientist are cloud computing, statistics and probability, machine learning and deep learning, advanced mathematics, data visualization, social media mining, database management, Python, R programming, Excel, query languages, data wrangling, communication skills, business acumen, analytical thinking, and teamwork.

What is the average salary of a Data Scientist in the US?

The national average salary of a data scientist in the US is $121,279 per year. The salary package varies depending on the location of employment, work experience, employer, role or job title, and industry.

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