The Data-Driven Leader: Leveraging Data and AI to Create Business Impact, by Sandro Saitta
Unlock the power of data and artificial intelligence to transform the way you lead and make business decisions.
Why I wrote this book
Why you need this book
Structure
No data, no AI
Leveraging data with AI
Different kinds of data
The myth of raw data
Methods of data collection
A typical data set
Understanding and mitigating data bias
Missing values and outliers
The issue with correlated features
In a nutshell
Why data quality matters
Case study: deduplication of hotel data
Where to address data quality issues
Improving data quality
In a nutshell
The power of summary statistics
Visualizing summary statistics
Correlation and PCA
Common pitfalls and misinterpretations
The case of correlation
A few words on outliers
Summary statistics are not enough
In a nutshell
Why visualize data?
Reading visuals: tips and tricks
Know your audience
Creating effective visuals
How to encode information
Data storytelling
In a nutshell
Key definitions in AI
A gentle introduction to machine learning
Types of machine learning models
How do machines learn?
Using ML to classify cats and dogs
Machine learning approaches
Building a machine learning model
Classification and regression
Measuring model accuracy
The challenge of overfitting
Five things to keep in mind
In a nutshell
Data-driven sales forecasting
Hotel revenue prediction
Online ads targeting
Exploring horizons
A never-ending story
In a nutshell
Understanding Generative AI
The GPT model
Applications of Generative AI
Enhancing Generative AI
Prompting
Common pitfalls
Detecting AI content
Patent and copyright issues
Limits and challenges of Generative AI
In a nutshell
The data science process
Key recommendations
An example in Human Resources (HR)
How to start a data project?
Tips for success
Be ready for change
In a nutshell
Limits of AI
The Case of Generative AI
AI trends
In a nutshell
Business leaders, executives, and decision-makers will find a proven, practical roadmap for understanding the essentials of data, artificial intelligence, and machine learning—without getting lost in technical jargon. Written with a strong business focus, this guide demystifies concepts like data quality, visualization, predictive analytics, and generative AI, showing how they directly impact strategy, operations, and innovation.
You’ll discover why “no data, no AI” is more than a slogan—it’s the foundation of every successful project. Through engaging examples and real-world use cases, the book explains how to collect the right data, improve its quality, and turn it into actionable insights. With clear explanations of summary statistics, data visualization techniques, and machine learning basics, readers gain the ability to ask the right questions and collaborate more effectively with data professionals.
From sales forecasting and customer targeting to the opportunities and pitfalls of generative AI and chatbots, this book brings theory into practice. It highlights best practices in data science, including project management, governance, and cross-functional collaboration, while also addressing the limits of AI and the importance of responsible, ethical use. Each chapter ends with key takeaways, ensuring readers not only understand the concepts but also know how to apply them within their organizations.
This is the definitive business introduction to data and AI—practical, insightful, and designed to help you turn information into impact.
There are many things to like about this clear and concise book, but my favorite aspect of it is that it describes all forms of AI and puts generative AI in perspective. If you want to understand the role of data, analytics, and AI in your organization, this is a great place to start.
Thomas H. Davenport
Distinguished Professor, Babson College
Research Fellow, MIT Initiative on the Digital Economy
Author of “Competing on Analytics”, “All In on AI”, and “All Hands on Tech”
AI without data is like a rocket without fuel. In “The Data-Driven Leader”, Sandro Saitta begins exactly where every book on AI should—with data—then takes you on a practical, well-illustrated, business-savvy journey into the future.
Douglas B. Laney, data, analytics, and AI strategy advisor
Author of “Infonomics” and “Data Juice”
“The Data-Driven Leader” tackles what I genuinely thought was impossible: making data and AI approachable for literally every professional out there. This book doesn’t just succeed at that impossible task—it has this wonderful side effect of making our entire field more inclusive and welcoming.
Tiankai Feng
Author of “Humanizing Data Strategy” and “Humanizing AI Strategy”
Dr. Sandro Saitta is a Data & AI advisor at viadata and helps organizations turn data and AI into business impact. He guides executives, builds data strategies, and drives execution across industries. Previously, he held leadership roles at the Swiss Data Science Center, Nespresso, Expedia, and SICPA, working at the crossroads of business value and technical innovation. A Ph.D. graduate from EPFL, Sandro co-founded the Swiss Association for Analytics, teaches at HEC Lausanne, champions data literacy, and serves on the executive committee of CDOIQ Europe, shaping the next generation of AI leaders.
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