Data Science book | Unique Big Data Analytics book | 432 pgs.
In 10 steps, this Data Science book teaches you how to detect relevant patterns using Data Science, algorithms, and machine learning.

Special hardcover edition: 432 pages
100+ color illustrations and schemas
Every major algorithm covered
Perfect balance of theory and reality
50+ best practices data science

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Data Science book

Framework of Data Science for Decision Makers & Data Professionals

Achieve data science success with this book

This brand-new Data Science book (2021) 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 don’t just get the theory, practical data science case studies are also covered. After reading the 10 chapters of this data science book, you will be prepared to start a data science project in your organization or those of your clients. Order this Data Science book here.

We’re generating more data than ever but only using 1%

The past 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%). Up to 25% of all data can help you make better decisions, and this Data Science book is going to help you achieve that. Data Science for Decision-Makers is going to help you achieve success with Data Science and Artificial Intelligence. Data Science success means more insight into the performance of your processes and overall performance and the continuous improvement and innovation of your products and business model using as much relevant data as possible.

Data science book product information

Format:
Number of pages:
ISBN:
Price:
Author:
Hardcover
432
9789082809169
€ 44.95

Daan van Beek MSc

Essential topics in this complete & unique Data Science book

With its 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.

Data Science & decision-making
Machine learning & AI
Algorithms explained
Deep learning & Data Science
Data Science organization
Data Science Roadmap
Maturity levels
Legislation: GDPR
Ethics & ethical principles
Data Science success factors
Agile working & data science
Robotic Process Automation
Business models & Data Science
Data Science & KPIs
Setting KPI targets
Data Science 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 Competencies
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.

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. Using the Data Science strategies in 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.

Data Science book provides overview of essential algorithms

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

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.

From Big Data to Zero Data

In addition to big data, small data and zero data are also rich sources of information that have the potential to generate valuable insights. Within these data sets and outside of the databases you can also find gold nuggets. Consider, for example, the products your customers didn’t buy, which is data that’s not registered in your database. Big Data Analytics also means analyzing and detected patterns in unstructured data such as photos, videos, sound recordings, website scrapes, emails, and other documents.

Target audience of this Data Science book

Every manager or professional that 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.

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Data Science book in higher education

This data science book was also written for teachers and students. Many colleges and universities have made this book required reading, but that doesn’t mean that it reads like a textbook. Practical matters are at the forefront. We’ve published a list of questions that students and readers can use to test their knowledge of the book.

What do our readers say?

“In important hallmark of this Data Science book is that every chapter contains interesting examples and recommendations for applications. This is the book’s important practical value. Van Beek shares his broad practical experience as a consultant.”

Piet Ribbers
Professor Emeritus Information Management

Framework of Data Science for Decision-Makers

This book doesn’t just put Data Science on the map, but it embeds each process in the concept of the intelligent, data-driven organization. The organizational and business aspects of data science applications are especially important to data science success.

Order this complete Data Science book now

Do you want to achieve success with Data Science, AI, and Big Data? Order Data Science for Decision-Makers and Data Professionals now. Make your organization intelligent and data-driven.

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About the author: Daan van Beek, MSc

Daan van BeekDaan van Beek, President 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. Daan regularly hosts AI & BI masterclasses in Europe, Singapore, South Africa, New York, and Paramaribo. He also teaches AI & Data Science at the renowned business schools TIAS and EUR.

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