Big data has become an essential component of modern business operations and is rapidly changing the way organizations operate.
With the increasing demand for data-driven insights, understanding the basics of big data has become a must-have skill for anyone in the business world.
Whether you’re a marketer, data analyst, or business leader, these books will provide you with the knowledge you need to navigate the big data landscape and make informed decisions.
In this post, we’ll be highlighting the top 7 books that will help you understand the basics of big data and how to apply it to your business.
So, let’s dive in and explore the best big data books for beginners in 2023.
1. Big Data: Concepts, Technology and Architecture
“Big Data: Concepts, Technology, and Architecture” is a comprehensive guide for data scientists, engineers, and database managers who want to learn about big data.
It is written by Balamarugan Balusamy, Nandhini Abirami R, Seifedine Kadry, and Amir Gandomi, the book is published by Wiley and is an ideal resource for business intelligence analysts, executives, and supervisors who need to make decisions based on large sets of data.
The book provides an in-depth look at the vocabulary, techniques, and technology surrounding big data, including the creation of structured, unstructured, and semi-structured data, data storage solutions, data processing, data analytics, machine learning, and data mining.
It also covers big data visualization using Tableau and emphasizes the application of big data in research.
The book is filled with explanatory case studies to demonstrate how the concepts have been applied in real-world situations, including dealing with common big data challenges like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns.
It also covers technologies such as Apache Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive, and the steps in the big data analytics lifecycle, such as preparing, extracting, transforming, analyzing, and displaying data.
2. Big Data Marketing: Engage Your Customers More Effectively and Drive Value
Big Data Marketing is written by Lisa Arthur and published by Wiley on October 7, 2013, is a comprehensive guide to using big data to improve customer service and drive business growth.
The book provides a strategic road map for executives looking to navigate the complex world of big data and harness its power to gain a competitive advantage.
It uses practical examples, easy-to-understand language, and additional resources to help readers understand the benefits of data-driven marketing and how to apply it in their organizations.
The book covers key topics such as using data to inform marketing decisions, adopting metrics as a motto, and improving customer experiences through data-driven strategies.
With its focus on improving ROI and managing marketing expenses, this book is a must-read for any marketer looking to take their skills to the next level.
3. Spark: The Definitive Guide: Big Data Processing Made Simple
“Spark: The Definitive Guide: Big Data Processing Made Simple” is a comprehensive handbook for developers and system administrators looking to learn about Apache Spark, an open-source cluster-computing platform.
It is written by the creators of Spark, Bill Chambers and Matei Zaharia, this book is published by O’Reilly and provides an in-depth look at Spark’s machine-learning library, MLlib, as well as the essentials of monitoring, adjusting, and debugging Spark.
Key takeaways from the book include learning the basics of big data with Spark, understanding the fundamental APIs of Spark, exploring Spark’s low-level APIs, learning how Spark functions on a cluster, and learning how to use MLlib to solve various machine-learning problems.
4. Big Data For Beginners
“Big Data For Beginners” is an ideal resource for anyone looking to understand big data from the ground level.
It is written by Vince Reynolds, this book is published by Createspace Independent Publishing Platform and provides an overview of big data analytics, the key challenges of big data, and how to generate business value through data mining.
After reading this book, readers will be able to analyze data from different sources and create datasets, as well as become proficient with important industry terms and applications and tools for a deeper understanding of big data.
5. Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
“Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results” is a book that provides a first-hand account of how big businesses use big data on a daily basis.
It is written by Bernard Marr and published by Wiley, this book examines the strategies and processes used by companies to learn about customers, improve manufacturing, foster innovation, increase safety and more, from technology, media, and retail to sports teams, governmental organizations, and financial institutions.
The book is set up to easily dip in and out and follows a similar format for each company profile, providing a detailed look at what information was used, what problem it solved and the process put into place to make it work.
It also provides technical specifics, difficulties, and lessons learned.
6. Ethics of Big Data: Balancing Risk and Innovation
The book “Ethics of Big Data: Balancing Risk and Innovation” written by Kord Davis and Dong Patterson, published by O’Reilly Media in October 2012.
This book delves into the ethical considerations brought about by the rise of big data and how businesses must reevaluate their privacy and identity-related decisions.
The authors provide strategies and tactics to guide companies in examining their current data practices and aligning them with their fundamental principles.
By understanding the impact of data handling on the reputation and profitability of a brand, readers will learn how to maintain trust with stakeholders while balancing the benefits of innovation with potential risks.
7. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Another book that delves into the topic of big data is “Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are” written by Seth Stephens-Davidowitz and published by Harper Luxe in May 2017.
This book offers a social perspective on big data by analyzing what can be inferred about human behavior from Google search data.
The author, a former Google data scientist, argues that information obtained from Google searches reveals fundamental aspects of the human psyche and how advances in analytical technologies and big data can change how individuals perceive the world.
The book has received numerous accolades, including being a New York Times Bestseller and Amazon Best Book of the Year in Business and Leadership.
