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Big data is a term that's been around for decades, but it wasn't until recently that we started to see its true potential. The growing popularity of cloud computing has led to an explosion in data storage and processing power, which has made it easier than ever for businesses large and small to collect and analyze their information.


As a result, many companies are turning from simple “enterprise applications” toward more complex solutions that involve machine learning (ML), semantic analysis (SA), natural language processing (NLP), and other techniques designed specifically for working with large amounts of data sets—or “big data.”


In this article, we will discuss the top 8 Big Data books to read to improve your knowledge and skill sets.


Big Data in Practice by Bernard Marr

This book doesn't focus on the fundamentals of digging up data, but rather on how corporations can put big data analytics to work right now. This book provides a practical overview of big data and highlights how businesses are putting this resource to work to achieve their goals in a variety of fields.


In addition to providing solutions for consumers' problems, the book provides technical specifics of the projects it has implemented. Students would be wise to study this book because it offers a realistic view of how to put big data to work.


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

This book will help you understand the power of big data in your life. It explains how we are all affected by this new technology and explores its implications for our economy, society, politics, and culture.


You’ll learn how to use big data to make better decisions about everything from consumer habits to healthcare issues like cancer screening or organ donation; from financial services such as banking or insurance premiums (to name just two examples); even transportation systems such as traffic congestion because it relies on real-time information about where people are going at any given moment in time which allows cities planners know how much room they need before filling up their infrastructure like roads or bridges.


Ethics of Big Data: Balancing Risk and Innovation by Kord Davis and Doug Patterson

This book goes beyond the standard fare of big data publications, which focus either on the technology behind it or on how it has impacted the industry at present. It deals with moral issues that arise when dealing with large amounts of data and the methods used to manage them.


Big data's effectiveness with audience members' private information is obvious, but its ethical repercussions are rarely if ever explored when applied broadly. This book will help you avoid privacy and ownership concerns by guiding you through data-handling approaches that are in line with your company's ideals and the practice of big data management.


Big Data Analytics with R by Simon Walkowiak

Those interested in using R for big data analytics will find this book, Big Data Analytics, invaluable. Readers who are unfamiliar with R will nevertheless gain a foundational understanding of data analysis and algorithm processing from this book. Since the R programming language is so statistically literate, it is becoming increasingly popular in the big data sector.


Beginning with introductory definitions of big data and R, the book proceeds through its narrative. But for those who are interested in learning more, the learning curve for applying the R language to large data research is quite steeply sloping.


Python for Data Analysis

If you are looking for a book that teaches you how to analyze data, this is the one. The authors of this book have created a complete guide on how to use Python for data analysis and analysis of big datasets. They start by explaining how to install and set up Python, then move on with their examples which include creating pie charts, bar graphs, and other visualizations based on your data set.


Once you understand these basics it's time for advanced topics like machine learning or neural networks so that you can get started applying them in real-life projects as soon as possible!


Big Data for Dummies by Judith Hurwitz, Alan Nugent, Marcia Kaufman, and Dr. Fern Halper

If you are just starting out in the field and want to learn more about the most widely used technologies, Big Data for Dummies is a fantastic resource. Using a comprehensive overview, the four specialists have incorporated fundamental ideas for comprehending big data approaches.


This book is fantastic for those who are new to the field of big data or are just starting out, but it may not provide as much depth for those who are already experts. However, it is one of the greatest books on big data for those new to the field.


Learning Spark

This book is a great way to get started on big data. It will teach you how to approach problems and find solutions using data science so that you can build better products and services for your customers.


The author explains what makes Spark so effective at processing large amounts of data quickly, which makes it ideal for businesses that need to analyze massive amounts of information quickly. This book also includes examples from real-world projects that use the technology behind these tools, which helps readers see where they could apply these concepts in their workflows.


Big Data Management by Peter Ghavami

Data analysts, engineers, and aspiring business leaders who want to use analytics to structure huge data would benefit greatly from Peter Ghavami's Big Data Management. Covering themes like privacy and data security throughout its life cycle, this book covers in-depth regulations, infrastructures, and contemporary tactics for dealing with big data.



If you are looking forward to making inroads into this profession, following the footsteps of true experts and studying the theoretical basis of the discipline would be useful. Hope these books will help you create a solid foundation for big data analytics and make a great start.


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