Top 10 Data Analytics Books You Must Know

“In the End, you should only Measure and Look at the Numbers that Drive Action, meaning that the Data tells you What you should Do Next” - Alex Peiniger

The ability to listen and comprehend the stories that Data has to tell you is no less than a valuable talent in contemporary times. In most cases, Data is found in a highly unrefined, unstructured and complicated form.

It takes the ability of Data Analysts to convert this non-usable mass of information into usable, exploitable and understandable entity. Thus, the skills of a Data Analytics expert is one of the highly sought after career choices in current times.

As you pursue these skills, certain texts and books can act as your reliable companions by helping you acquire a better grip over the Data Analytics subject matter.

Keeping this in mind, we have come with this carefully curated list of some of the Best Data Analytics Books, which you should definitely lay your hands on if you are looking to enter this field.

Want to know about what skills should you acquire as a Data Scientist?; read our blog on “Top Data Analyst Skills You Need to Know”

In this blog, we shall look 10 Best Books on Data Analytics. The list shall include Data Analytics Books for Beginners as well as Books on Data Analytics for the intermediate and the advanced level.

Top 10 Data Analytics Books

Data Analytics Made Accessible

• Author: Dr. Anil Maheshwari
• Browse through any article on Books on Data Analytics and you shall definitely find the name of this book. It is considered to be one of the best Data Analytics Books for Beginners. 
• The wealth of information and the easy-to-follow narrative of the book, has led many universities to adopt it as their formal textbook.
• The USP of the book is its reliance on real-world examples instead of hypothetical situations for explaining key Data Analytics concepts.
• The layout of the book is well organized and structured, as would be like a semester long college course. 
• As an extremely useful Data Analytics Books, it provides for brainstorming case study exercises as well as review questions. 
• Moreover, the text also offers Python and R Data Mining tutorials for beginners.
• The book was last updated in 2021 and covers some of the highly significant and relevant topics like Big Data, Career in Data Science, Data Privacy, Artificial Intelligence and so on.

Big Data: A Revolution That will Transform How We Live, Work, and Think

• Author: Viktor Mayer-Schönberger and Kenneth Cukier
• This text is one of the highly recommended Books on Big Data Analytics. 
• The book goes beyond the business realm and takes a very practical approach in arguing that Big Data has revolutionized the life of the entire human species. 
• The author adopts a very pragmatic path in making his point on how Big Data can be optimally exploited for bettering the quality of human life in general. 
• Instead of most Books on Data Analytics which focus on the technical aspects of quantifying and measuring data; this book largely emphasis on the definition of Big Data, its characteristics, the value it holds for the future as well as the way in which it would possibly change the Data Management process.

If you are someone seeking to make your way through the Data Analytics field; read our blog on “How to become a Big Data Analyst?: Come Find the Answers”

Too Big to Ignore: The Business Case for Big Data

• Author: P. Simon
• This is another of the classic books on Big Data Analytics. 
• The author makes use of real life instances in order to depict the usage of Big Data by local governments and companies. For instance, the Boston Government took up the cause of fixing potholes on the basis of data fed by residents of the city in their smartphones. 
• As the name of the book suggests, the text is a must read for all those denying the advantages of Big Data as well as those who are completely blown away by the merits of Big Data. 
• The author has stressed in unequivocal terms that it has become indispensable for business organizations to factor in the aspect of Big Data. It is not simply a chance innovation, but in fact has evolved as a significant manner in which business is being conducted.

Business Unintelligence: Insight and Innovation beyond Analytics and Big Data

• Author: Dr. Barry Devlin
• This is one of those slightly unconventional Data Analytics Books. Instead of being counted as one of those best books on Data Analytics for Beginners; it is in fact a book suited for seasoned Business Intelligence professionals. 
• As one of the well-known books on Data Analytic thinking, the author traces the history of the field. He elaborates on the past, present and future of the domain. 
• One of the central arguments made by the author in this book is that business decisions should be based on the prudent combination of intuitive emotional sources as well as rational data-based sources. Thus, he refutes the over-generalizing assumption that decisions should be based on data alone. 
• The author discusses the genesis of the biz-tech ecosystem as well as offers practical suggestions on the usage of Big Data.

The Hundred-Page Machine Learning Book 

• Author: Andriy Burkov
• This is yet another reputed books about Data Analytics, which more precisely deals with the topic of Machine Learning. 
• The author is a seasoned expert in the field of Machine Learning and Artificial Intelligence and does an excellent job in presenting information on these technologies in the most lucid and digestible forms. 
• It is a short read and yet it touches upon a wide range of topics within the ML field in as comprehensive a manner as possible. 
• Some of the key areas highlighted in the text include, neural networks, hyperparameter tuning, supervised and unsupervised learning, cluster analysis and so on.

Creating Value with Social Media Analytics: Managing, Aligning, and Mining Social Media Text, Networks, Actions, Location, Apps, Hyperlinks, Multimedia, & Search Engine Data 

• Author: Gohar F. Khan
• This is one of those Best Data Analytics Books which teach you how to optimally utilize data-based metrics and insights through social media platforms. 
• This book can be an excellent help in helping you develop a better understanding of the strategies, theories, techniques and concepts which go into deriving business value from social media. This value is best manifested in the form of generating leads, undertaking business decisions, improving client loyalty and increasing traffic. 
• As one of those prominent books on Big Data Analytics, this text trains you in leveraging Big Data for refining your social media strategy and deriving utmost advantage from the same.

Artificial Intelligence: A Guide for Thinking Humans

• Author: Melanie Mitchell
• As the name suggests, this book is one of the best Artificial Intelligence Books. However, it has still been included in this list of Data Scientists Books because any understanding of Data Analytics is bound to remain incomplete without comprehending the impact of technologies like AI on the field of Data Analytics. 
• The author does an outstanding job in helping the reader understand such complex concepts as Computer Vision Models, Neural Networks, Natural Language Processing (NLP) and so on. 
• Consequently, the USP of the book lies in the way in which the author has sought to tackle some of the most pressing questions within the field of Artificial Intelligence. In doing so, he has logically highlighted a discrepancy between the hype surrounding AI and the real accomplishments within the field.

Data Smart: Using Data Science to Transform Information into Insight

• Author: J.W. Foreman
• This can be considered as a useful Data Analytics Books for those at the intermediate to the advanced level. 
• The text provides some really good recommendations on the application of specific analytic techniques for effectively managing data. 
• The book can be seen as a carefully structured tutorial, providing real world instances for individuals who must work with data sets. 
• The content does require the reader to possess some minimal amount of technical knowledge in Excel and Applied Mathematics. 
• The text offers a range of techniques and strategies and all of it with the help of a spreadsheet. This includes graph modularity, ensemble models, genetic algorithms and nonlinear programming, forecasting, clustering, seasonal adjustments, data mining in graphs, prediction intervals, supervised AI through logistic regression and so on. 
• The book is quite useful in the sense that it gives an idea on how one can begin with the analysis part by making use of Microsoft Excel itself. While the tool might not be useful in handling huge volumes of data, but it is definitely a good starting point.

Python for Data Analysis

• Author: Wes McKinney
• This is one of the Best Data Analytics books for Beginners, especially those who are new to Python programming. 
• It is often considered to be a foremost text of choice on Data Wrangling with NumPy, IPython and pandas. 
• The reader will be able to learn to perform various activities on Python datasets, including manipulation, crunching, cleaning and processing of data. 
• The Python library is considered to be no less than a treasury and the book offers lessons on the creation of interactive, animated and static data visualization with Matplotlib.

An Introduction to Statistical Methods and Data Analysis

• Author: R. Lyman Ott and Michael Longnecker
• This is yet another helpful Business Analytics books for Beginners which provides a broad overview of statistical methods. 
• It is a great read for students who have no prior grounding in statistics. 
• The first few chapters of the book are as carefully structured and are as easily comprehensible as texts on introductory statistics courses. Added to it, there are numerous real world examples and case studies which would help you sharpen your understanding of the key concepts. 
• The book can be useful in terms of preparing you for different challenges, often confronted in research projects. Additionally, you will also be able to understand the process of data-driven decision making. 
• In the later part of the text, you shall be introduced to experimental design and regression modeling.

Conclusion

The field of Data Analytics is an expansive one. There are so many angles to the domain that the list on Data Analytics Books could perhaps be an endless one. For the purpose of convenience, here in this blog, we have touched upon some of the best Data Analytics Books which helps you establish your foothold in the field right at the foundational level. Some of these books on Data Analytics are slightly offbeat in terms of dealing with topics like Machine Learning and Artificial Intelligence. However, given the ongoing innovations in these latter domains, any understanding of Data Analytics is bound to remain incomplete without taking into consideration, these technologies. 

The door of a Data Analyst is an all-embracing one. This implies that individuals from technical and non-technical backgrounds alike can seek to make a career in the field if they are passionate about the world of data. 

If you too are someone who lacks a conventional STEM degree and is still looking to make it big in the field of Data Analytics, do read our blog on “How to become a Data Analyst without a degree?: A Step-by-Step Guide”

We, at Syntax Technologies, provide each and every individual, irrespective of their background to take their first step in the domain of Data Analytics, with our foundational Data Analytics and Business Intelligence course. Enrol now: