The Decision Maker’s Handbook to Data Science: New Book Ditches Jargon and Buzzwords; a Layman’s Guide to the “Data Revolution”


United Kingdom – The terms “big data” and “machine learning” twist most non-technical decision makers into a frenzy of fear and confusion. But while they’re the buzzwords of the moment, the trend toward data-driven business decisions is actually the way of the future, and now it’s a competitive edge anyone can deploy with ease.

It’s all down to a new guide by Dr. Stylianos Kampakis, ‘The Decision Maker’s Handbook to Data Science: A guide for non-technical executives, managers and founders’, which gives laypeople everything they need to incorporate data science into their day-to-day business activities.


Have you ever felt confused by terms such as “data science” and “big data”? What is really the difference between AI and machine learning? How can you hire a good data scientist and how do you build a data-driven organisation? Have you ever thought you’d like to use data-science, but you don’t know where to start?

The Decision Maker’s Handbook to Data Science was written specifically for you. It covers all the topics that a non-technical decision maker needs to know in order to use data science within an organisation.

Driven by the author’s 10+ years of experience, the book’s aim is to demystify the jargon and offer answers to all the most common problems and questions that decision makers face when dealing with data. Topics include:

1) Explaining data science. Demystifying the differences between AI, machine learning and statistics.

2) Data management best practices.

3) How to think like a data scientist, without being one.

4) How to hire and manage data scientists.

5) How to setup the right culture in an organisation, in order to make it data-centric.

6) Case studies and examples based on real scenarios.

Data science, machine learning and artificial intelligence are amongst the main drivers of the technological revolution we are experiencing. If you are planning to collect and use data within your company, then the Decision Maker’s Handbook to Data Science will help you avoid the most common mistakes and pitfalls, and make the most out of your data.

“The bottom line is that every manager and decision maker in today’s world needs to learn about data science,” explains the author. “Data is all around them, even being collected in ways they don’t know about – and this data holds the answers and direction to their biggest business challenges. Data science can be simple, and in this book I made it my job to help anyone understand it and embrace the data they have for better decision making.”

Continuing, “Feedback has been extremely positive, with many people who’ve never previously used the data they’re harnessing contacting me with success stories, of using it to take their decision making to an entirely new level.”

Indeed, reviews have been impressive. Franklin Karkada comments, “The book is extremely interesting. Within reading the 25% of the book, I have a good overview of the data science and how it can support the decision making process. Simple and very business oriented. i am sure any management/ business person without data science background would be able to understand the book. I like the simplicity in which the author has explained the overview of data science from the high level point of view and at the same time he has covered some good understanding of the low level things.”

Another reader adds, “Well written and the explanations are clear. It is written to help from the perspective of a manager or executive, and you won’t find many other books like it.”

‘The Decision Maker’s Handbook to Data Science: A guide for non-technical executives, managers and founders’ is available now:

For more information, visit the author’s official website:

About the Author:

Dr. Stylianos (Stelios) Kampakis is a data scientist who is living and working in London, UK. He holds a PhD in Computer Science from University College London, as well as an MSc in Informatics from the University of Edinburgh. He also holds degrees in Statistics, Cognitive Psychology, Economics and Intelligent Systems. He is a member of the Royal Statistical Society and an honorary research fellow in the UCL Centre for BlockchainTechnologies1. He has many years of academic and industrial experience in all fields of data science: statistical modelling, machine learning, classic AI, optimization and more.

Stylianos’ academic experience ranges across various domains. He is one of the foremost experts in the area of sports analytics, having done his PhD in the use of machine learning for predicting football injuries. He has also done work in the area of neural networks, computational neuroscience and cognitive science. He is also doing research in blockchain and more specifically in the area of tokenomics, where he studies topics such as the best mechanisms for handling volatility in token economies and evaluating Initial Coin Offerings (ICOs).

In terms of industrial experience, Stylianos has worked on a wide range of problems. Some examples include using deep learning to analyze data from mobile sensors and radar devices, to recommender systems, to natural language processing for social media data. He has also done work in the areas of econometrics, Bayesian modelling, forecasting and research design. He also has lots of experience in consulting for startups, having worked with companies that have raised millions in funding.

Stylianos is also very active in the area of data science education. He the founder of The Tesseract Academy2, a company whose mission is to help decision makers understand deep technical topics such as machine learning and blockchain. He is also teaching “Social Media Analytics”, and “Quantitative Methods and Statistics with R” in the Cyprus International Institute of Management.