Achieve data science success with this book
This brand-new Data Science book covers every essential organizational and technical facet of (big) Data Science, AI, and machine learning. Learn how to build an intelligent, data-driven organization using the many examples and applications of data science and algorithms in this book. You will not only learn about the theory but will also have access to practical data science case studies. After reading the 10 chapters of this data science book, you will be very well prepared to start a data science project in your organization or your clients’ organization. Order this Data Science book here.
What is the book about?
This book will help you better understand the essence of data science and AI so that you can reap the advantages by implementing new solutions and applications in your organization. In ten clear steps, the author describes the path to creating a mature, intelligent, and data-driven organization. You can become a part of a smarter organization and a more fair and intelligent world. To BI or not to be, that is the question. In the end, what matters is what you get out of it, not what I have put into it. Hopefully, you’ll be converted into an AI and data science enthusiast. Check out the reviews at the end of the page, to see what readers thought about our book!
Data science book product information
Do you prefer the Kindle or paperback edition? Order this Data Science book on Amazon.
We’re generating more data than ever but only using 1% of it
In the last two years, people have generated more data than in the entire history of mankind before that. However, organizations only use a fraction of that data (1%). The book Data Science for Decision-Makers is going to help you achieve success by showing the way to better organization performance. Learning about Data Science will help you obtain continuous improvement and innovation for your processes, products, and business model.
Target audience
Every manager or professional who wants to increase their returns on data will find this data science book a valuable lifeline. The book is a must-read for (business) consultants, Data Science consultants, Data Scientists, AI consultants, (business) controllers, quality managers, BI consultants, project managers, Chief Data Officers, CIOs, and other executives.
Higher education
This data science book was also written for teachers and students. Many colleges and universities have made this book mandatory, but that doesn’t mean that it is like a textbook. Practical matters are at the forefront. We have a list of questions (available on request) that students and readers can use to test their knowledge of the book.
Achieving results with Data Science
After reading this Data Science book, you’ll know exactly how the processes behind Big Data analytics and Data Science work. You’ll also have learned more about the analysis tools and you’ll be familiar with the architecture. You will have gained insight into the practical case studies that illuminate the theory. You’ll also know how to apply artificial intelligence and machine learning models and what the benefits are. Once you’ve read this Data Science book you’ll be able to separate the hype from the tangible benefits of Data Science and artificial intelligence. Finally, you can easily determine if and how Data Science & Analytics can work for your organization.
Predict the future using Data Science
Data Science isn’t just the future, it’s the here and now. Tactically implementing Data Science can lead to enormous profits. By using the Data Science strategies of this book, your organization can get a 360-degree customer view or predict machine outages, for example. Big Data analysis can reveal trends and patterns that had gone unnoticed. Data Science can also help you understand customers, substantially improve your company’s performance, predict the behavior of website visitors, and make data-driven decisions company-wide.
Essential algorithms of the Data Science book
Data Science for Decision-Makers covers every essential algorithm and related jargon. Gain a better understanding of the development process for the proper application of Data Science and AI techniques.
✪ Image processing
✪ Decision trees
✪ Supervised learning
✪ Unsupervised learning
✪ Overfitting and underfitting
✪ Linear regression
✪ Naive Bayes
✪ Text mining
✪ Random forest
✪ Genetic algorithms
✪ Probability
✪ Bayesian Network
✪ Logistic regression
✪ Gaussian Naive Bayes
✪ Neural networks
✪ Natural Language Processing
✪ Business rules
✪ Accuracy
✪ Cluster analyses
✪ Nearest neighbor search
✪ Reinforcement learning
Essential topics in this complete Data Science book
With 432 pages, this Data Science book can be considered quite comprehensive. The author extensively covers the following topics and provides clear explanations about the terminology underpinning Data Science, BI, Artificial Intelligence (AI), machine learning, and (Big) Data Analytics. You can start seeing the forest for the trees once again.
✪ Machine learning & AI
✪ Algorithms explained
✪ Deep learning
✪ Data Science organization
✪ Data Science Roadmap
✪ Maturity levels
✪ Legislation: GDPR
✪ Ethics & ethical principles
✪ Data Science success factors
✪ Agile working & data science
✪ Robotic Process Automation
✪ New Business models
✪ Setting KPI targets
✪ Data Strategy & policy
✪ Data Science architecture
✪ Cloud & Data Science
✪ ETL & Big Data Science
✪ Data Lakes & data quality
✪ Data warehousing
✪ Data Governance (DMBOK2)
✪ Data virtualization
✪ Descriptive Analytics
✪ Predictive Analytics
✪ Prescriptive Analytics
✪ Data Science roles
✪ Data Science tools
✪ Data Science applications
✪ Project management
✪ Data Science & AI risks
✪ Data Science Governance
✪ BICC & Data Science
✪ Data Science innovation
✪ Continuous Improvement
✪ Social infrastructure
✪ Future of Data Science
✪ Datafication of society
The book contains over 100 color illustrations and 50 (international) best practices and is bound as a deluxe hardcover.
Order this complete Data Science book now
Do you want to achieve success with Data Science, AI, and Big Data? Order the book ‘Data Science for Decision-Makers and Data Professionals’ now and make your organization intelligent and data-driven.
About the author: Daan van Beek MSc
Daan van Beek, CEO of Passionned Group, wrote this Data Science book based on over 20 years of experience as a consultant and manager. You won’t find more knowledge about creating an intelligent, data-driven organization through the application of Data Science, AI, and Big Data anywhere else. Daan regularly hosts AI & BI masterclasses in Europe, Singapore, South Africa, the United States, and Suriname. He also teaches AI & Data Science at the renowned business schools TIAS and EUR.
Reviews about Data Science book
Maissa Seghir | Student: Because I want to pursue a master's in data analytics after my bachelor's degree, this book has been the perfect first step to gain knowledge about Business Intelligence (BI), Artificial Intelligence (AI), big data analytics, machine learning, and Data Science. I definitely recommend the book; the knowledge you gain from it is highly relevant to today's world and job market.Adolf Waaldijk | Fiit BV: I would like to compliment the author of The Data Science Book. I purchased the book due to a shift in my responsibilities in the latter half of this year, as my focus is now on the sales of 'Wyn.' As the Director/COO of Fiit BV, the company behind the development of the BI platform 'Wyn Enterprise,' I don’t have an IT background, so I’ve been working hard to get up to speed. I've read about a third of the book so far, and it has completely captivated me. The content is engaging, and the writing style makes it an enjoyable read.
Mark van der Veen | Utrecht University of Applied Sciences: I have been using the old and new versions for years for the Business Intelligence course at the part-time HBO-ICT Business Information Management. The book realistically illustrates how creating value from data is process and organization oriented. If you use this correctly, with the tools from Daan's book, you will be ready to continuously capitalize on the value that you can get from your data through the application of BI technology. Recommended for anyone who wants to see BI (and also applicable to AI) as a structural part of their organizational capabilities.
Chris Bil | Hanze University of Applied Sciences Groningen: Very good, interesting, clear and informative book!
Bonny | : I think it's an incredibly interesting book, which can really be used as a guide to implement BI within the organization, so that the organization can eventually become data-driven. It is clearly written, making the steps easy to follow. It also gives clear insights into why BI is important within an organization, allowing you to use this for adoption within an organization. It gives concrete examples, allowing you to translate theory into practice. All in all, a pleasant book to read and provides the right tools for organizations to start working data-driven.
Jeroen Schothuis Qc Msc MBA | : I have now read six chapters. My compliments for the quality offered in terms of content and structure. It is clear to me that the writer has a lot of practical experience and also showcases this in addition to the accessible theoretical frameworks. A must for controllers/financial manager/CEOs to study and implement this material in their organization.
Peter Mulder | Information manager: What struck me, you didn't just take a detailed and structured approach, you took an exceptionally detailed and structured approach! What appealed to me is that I now have a very complete reference book in the field of BI and AI. Point of improvement: if your target audience is also at the strategic management level, I would also add some kind of "management summary".
Yolanda Stuijt | docent Business & IT Management | Amsterdam University of Applied Sciences: I started the Data Science book and already used it in my classes to explain KPIs. The topics are carefully explained in understandable Dutch. The illustrations are clear, easy to explain and of good quality to put in a ppt slide! If I have an English speaking class I can use the english illustrations. So very useful!!! I improved one of my classes "BI tools" by using chapter 4 "data science tools and applications". Mapping the BI tools to the decision making process gives a good overview of what where which tool can be used and with the BI applications, I can explain to students what type of analysis takes place in their project. Section 4.3 is learning material for me because the students learn this ealier in the curriculum. Actually, I use this book as a library to browse and grab what I need! Super nice!!!
Henk Wattimury | : Compliments on your language and writing style. Clear and easy to follow. I started the last half. Technical part about dbms and the data warehouse fabric has piqued my interest. The schematic illustrations perfectly chosen.
