Data Analytics Books

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We have compiled the list of Best Reference Books on Data Analytics subject. These books are used by students of top universities, institutes and colleges. Here is the full list of best books on Data Analytics along with reviews.

Kindly note that we have put a lot of effort into researching the best books on Data Analytics subject and came out with a recommended list of best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on “Data Analytics” as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.

List of Data Analytics Books with author’s names, publishers, and an unbiased review as well as links to the Amazon website to directly purchase these books.

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1. Data Analytics and Visualization

1. “Analytics: Business Intelligence, Algorithms and Statistical Analysis (Predictive Analytics, Data Visualization, Data Analytics, Business Analytics, Decision Analysis, Big Data, Statistical Analysis)” by Todd J Blatt

“Analytics: Business Intelligence, Algorithms and Statistical Analysis (Predictive Analytics, Data Visualization, Data Analytics, Business Analytics, Decision Analysis, Big Data, Statistical Analysis)” Book Review: This book is a detailed study of analysis and various related elements. The readers get to know how different elements such as analysis, business intelligence, algorithms and statistical analysis are interlinked with each other. The book helps in a greater understanding of these elements and how they work. The book begins by describing the challenges and risks associated with analytics so that readers have an idea about what they are going to study in the rest of the book. Then it goes on to include different types of analytics-Predictive, Descriptive and Prescriptive Analytics. A separate chapter on integrating business and analytics is also given in the book. Other important topics such as the benefits of business intelligence, data mining, data integration, data visualization are also described. The book is useful for self employed businessmen, data analysts and developers.

2. “Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance” by Bernard Marr

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“Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance” Book Review: This book focuses on converting big data into real world results. It teaches how to get big data to get the best, real-world business results and putting that in place to improve performance. The book gives the readers a clear understanding and step-by-step approach to building their own big data strategy. It discusses how companies need to clearly define what it is they need to know. It also describes how companies can collect relevant data and measure the metrics that will help them answer their most important business questions. The real world case studies discussed in the book help the readers understand the concept of big data in a practical manner. The book is useful for data analysts, researchers and practising engineers working with big data and related subjects.

3. “Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data” by EMC Education Services

“Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data” Book Review: The book offers an overview of big data technologies and explains what is needed to succeed with big data. It gives examples of both successful and failed data practices undertaken by startups, online firms and large companies. It provides a comprehensive overview of visualizing and presenting the data in a more reasonable manner. It also discusses in detail the discovering and analyzing of data science and big data analytics. The book is useful for students, researchers and data analysts.

4. “Tableau Your Data: Fast and Easy Visual Analysis with Tableau Software” by Daniel G Murray

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“Tableau Your Data: Fast and Easy Visual Analysis with Tableau Software” Book Review: This book guides the reader how to use Tableau Software toolset for data visualization in an effective manner. It covers the core features of data analytics along with some advanced features and techniques. The book illustrates various practices for creating and sharing effective visualizations that help in supporting timely business decision-making. The features included in the book are illustrated with real-world case studies that provide application based understanding of the subject matter. The book is useful for software developers, engineers, students and researchers.

5. “Big Data Analytics” by Parag Kulkarni and Sarang Joshi

“Big Data Analytics” Book Review: This book starts with a detailed and complete introduction on Big Data Analytics. Then it describes data mining and modelling that includes an important aspect of big data analytics. The next two chapters are big data mining-application perspective and long live the king of big data: the context. Distributed high dimensional data clustering for big data and machine learning and incremental learning with big data are also discussed comprehensively. The last chapter describes analytics in today’s business world that provides a practical perspective of the usage of big data. The book ends with a conclusion. The book would be useful for software developers, engineers, students and researchers.

6. “Python for Data Science for Dummies” by John Paul Mueller and Luca Massaron

“Python for Data Science for Dummies” Book Review: This book teaches the reader how to use Python programming to acquire, organize, process, and analyze large amounts of information. It also focuses on using basic statistics concepts to identify trends and patterns. The readers will learn the python development, how to manipulate data and design compelling visualizations. By the end of the book, they will be able to solve scientific computing challenges. The book also explains objects, functions, modules, and libraries and their role in data analysis. The book is useful for anyone interested in learning about data analysis and Python.

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7. “Learning Predictive Analytics with R” by Eric Mayor

“Learning Predictive Analytics with R” Book Review: This book is a beginner’s guide to data analytics. It describes the different features of unstructured data mining while examining the practical aspects of Big Data. The text begins with the introduction to the subject and explores the concept of data mining methods and models along with the applications. It then goes into detail on other aspects of Big Data analytics, such as clustering, incremental learning, multi-label association and knowledge representation. The book finally ends with a discussion on the areas where research can be explored. The book is designed for the senior level undergraduate, and postgraduate students of computer science and engineering.

8. “Data Analytics : The Complete Beginner’s Guide – Step By Step Instructions” by Byron Francis

“Data Analytics : The Complete Beginner’s Guide – Step By Step Instructions” Book Review: This book provides a complete and detailed guide to data analytics for beginners. It includes real-world examples at the beginning of each chapter so that readers get an application based understanding of the subject matter. It also highlights data analytics techniques that really provide added value in business environments. The book reviews some underlying principles of data analytics in a blend of theoretical and practical knowledge. The book is useful for the senior level undergraduate and postgraduate students of computer science and engineering.

9. “Data Analytics : A Quick-start Beginner’s Guide” by Andy Hayes

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“Data Analytics : A Quick-start Beginner’s Guide” Book Review: This book is a beginner’s guide to data analytics. It describes the different features of unstructured data mining while examining the practical aspects of Big Data. The text begins with the introduction to the subject and explores the concept of data mining methods and models along with the applications. It then goes into detail on other aspects of Big Data analytics, such as clustering, incremental learning, multi-label association and knowledge representation. The book finally ends with a discussion on the areas where research can be explored. The book is designed for the senior level undergraduate and postgraduate students of computer science and engineering.

10. “Getting Started with Greenplum for Big Data Analytics” by Sunila Gollapudi

“Getting Started with Greenplum for Big Data Analytics” Book Review: This book is a beginner-friendly guide that provides a basic understanding of Greenplum. The topics are explained with the help of Data Warehousing and Business Intelligence platforms. It explains Big Data Analytics through database design and programming as well as analytics tools like R and Weka. With a blend of technology and domain expertise, the book explains all the basic aspects of Greenplum in an application-oriented manner. The book is useful for data scientists and data analysts.


2. Educational Data Analytics

1. “Data Analytics” by Anil Maheshwari

“Data Analytics” Book Review: This book explains the basic principles of data analytics. The chapters in this book are designed for a one-semester graduate course. It covers topics like business intelligence and its applications across industries and data mining. It also explains data processing chains, data warehousing and artificial neural networks. It describes statistical regression modeling techniques and cluster analysis. There are review questions at the end of each chapter and solved examples throughout the chapter. This book is suitable to those who want to understand data based decision-making for their business. But have no expertise with software tools. The book does not contain any programming code.

2. “DAX: Your Definitive Guide To LEarn And Write Dax (DAX, Big Data, Data Analytics, Business Intelligence)” by Adrian Venice

“DAX: Your Definitive Guide To LEarn And Write Dax (DAX, Big Data, Data Analytics, Business Intelligence)” Book Review: This book helps the reader to write and understand DAX. It covers all the basic measures, calculation you need to know as a beginner. The chapters included are how DAX works in power pivot, DAX syntax, data types and date and time functions. It also described various functions used in DAX like information, filter, logical, text and parent child functions. At the end of every chapter there are dax exercises and puzzles for innovative learning. It also contains tips and troubleshooting to keep in mind. This book is suitable for beginners in DAX.

3. “Graphesis – Visual Forms of Knowledge Production (metaLABprojects)” by Johanna Drucker

“Graphesis – Visual Forms of Knowledge Production (metaLABprojects)” Book Review: This group describes the analysis of graphical knowledge. It highlights the principles by which visual formats organize meaningful content. It explains in detail the graphical user interface (GUI) format. This format is commonly used in most of the electronic divides. The book covers the reason how visual forms shape knowledge, our behavior, and even our identity. The topics are covered in the form of case studies on how graphic languages can serve fields where qualitative judgments take priority over quantitative statements of fact.

4. “Integrierte Business-Informationssysteme: ERP, SCM, CRM, BI, Big Data Analytics – Prozesssimulation, Rollenspiel, Serious Gaming” by Klaus-Dieter Gronwald

“Integrierte Business-Informationssysteme: ERP, SCM, CRM, BI, Big Data Analytics – Process Simulation, Rollenspiel, Serious Gaming” Book Review: This book covers the latest developments in big data methods and in-memory computing. It is technology-driven innovations that permanently change corporate structures and their competitive situation. It explains the implementation of Supply Chain Management (SCM), Big Data Analytics (BDA) and Enterprise Resource Planning (ERP). These are implemented using standardised software systems. It also explains management-oriented thinking and acting which is required to understand the above topics. It explains in a business perspective for example as members of the executive board of a virtual model company for better understanding of the students.

5. “Serious Games Analytics (Advances in Game-Based Learning)” by Christian Sebastian Loh and Yanyan Sheng

“Serious Games Analytics (Advances in Game-Based Learning)” Book Review: This book contains research on how dta of game play can be used for performance measurement, assessment, and improvement. Existing experimental and emerging conceptual frameworks are used to devise the results. These are obtained from fields like computer science, software engineering and educational data mining statistics. Serious games is an emerging field where the games are created using sound learning theories and instructional design principles. These are used to maximize learning and training success. This book lets the readers know how stakeholders know what play-learners have done in the game environment and many other interesting information.

6. “Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data” by Andreas Holzinger and Gabriella Pasi

“Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data” Book Review: This book contains the data from the Third Workshop on Human-Computer Interaction and Knowledge Discovery held in Maribor, Slovenia, in July 2013. 20 revised papers are described from 68 submissions of the workshop. The papers are reviewed and organised on topics of human-computer interaction and knowledge discovery, knowledge discovery and smart homes, smart learning environments, and visualization data analytics.

7. “Computer Assisted Assessment — Research into E-Assessment: International Conference” by Marco Kalz and Eric Ras

“Computer Assisted Assessment — Research into E-Assessment: International Conference” Book Review: This book contains data from the International Conference on Computer Assisted Assessment, held in Zeist, The Netherlands, in June/July 2014. 16 revised full papers are reviewed and organised from numerous other submissions. The topics discussed in the book are large-scale testing facilities in higher education, formative assessment for 21st century skills and future trends for technology-enhanced assessment. It also covers the latest advancements of technologies and practical experiences.

8. “Bayes Theorem : A Quick-Start Beginner’s Guide” by Andy Hayes

“Bayes Theorem : A Quick-Start Beginner’s Guide” Book Review: This book describes the applications of the theorem. These are not limited to the financial sector only. Bayes’ theorem gives the probability of an event based on information that is or may be related to that event. The formula can be used to see how the probability of an event occurring is affected by new information. This book is suitable for the beginners who have just started learning it. The book contains many solved examples and exercises for practice.

9. “Data Mining and Learning Analytics: Applications in Educational Research (Wiley Series on Methods and Applications in Data Mining)” by Osmar R Zaïane and Samira ElAtia

“Data Mining and Learning Analytics: Applications in Educational Research (Wiley Series on Methods and Applications in Data Mining)” Book Review: This book describes the impacts of data mining on education. It covers applications in educational research teaching, and learning in this field. It also explains the challenges faced and provides measures in data mining (DM) within educational mandates. The book discusses the four guiding principles of data mining that are prediction, clustering, rule association, and outlier detection. It contains case studies from various fields like Business, Humanities, Health Sciences and Physical Sciences that highlight the success of this field. This book features supplementary resources including a primer on foundational aspects of educational mining and learning analytics. It is designed by the experts of this field. This book is suitable for both scientists in EDM and teachers to improve education and advance educational research.

10. “Data Analytics Applications in Education” by Jan Vanthienen and Kristof De Witte

“Data Analytics Applications in Education” Book Review: The generation of data in huge amounts in recent times has led to the rise of new quantitative and statistical techniques called data analytics. This method of decision making allows organizations to exploit big data analytics in their evaluation and decision processes. Data analytics techniques can be used to enhance the student’s learning process by providing real-time feedback and support for the teacher. The teacher can trace the learning of the student and work on the loose areas. The book stresses that data analytics in education should not be the domain of a single discipline. This book is useful to philosophers, computer scientists, and sociologists. This book provides methods to face the challenges ahead. Data analytics can be used as a very useful tool in the educational sector.

People who are searching for Free downloads of books and free pdf copies of these books on Data Analytics – we would like to mention that we don’t have free downloadable pdf copies of these good books and one should look for free pdf copies from these Authors only if they have explicitly made it free to download and read them.

We have created a collection of best reference books on “Data Analytics” so that one can readily see the list of top books on “Data Analytics” and buy the books either online or offline.

If any more book needs to be added to the list of best books on Data Analytics subject, please let us know.

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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