Most Recommended Big Data Books

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Most Recommended Big Data Books for Beginners and Professionals

In this article, I will provide the list of the Most Recommended Big Data Books for Students, Beginners, and Professional Developers. If you want to start your carrier in Data Science then writing code using Big Data might be confusing for a beginner. Books are the best friend of students as well as developers and the first mode of learning new languages, and technologies and nothing can beat books when it comes to educating. It is the reason most experienced Big Data Professionals recommend reading books for learning Big Data. 

Combining the best Big Data books along with articles, tutorials, and videos, you will get an excellent path to learn Big Data. Some of the books just give an overview of various Big Data concepts, while some other jQuery books go into the depth of each Big Data concept.

There are hundreds and thousands of Big Data books available on Amazon or Internet or any other e-commerce site. And as a beginner, you might be confused to choose the right book to start learning Big Data. Here, we are giving you the list of Big Data Books based on the experience of Learners and Professionals. If you still haven’t put together your reading list for 2021, we’re here to help with our choice of the best-recommended books for Big Data.

1. Big Data and Analytics

Big data is a term used for massive mounds of structured, semi-structured, and unstructured data that has the potential to be mined for information. The real power lies not just in having colossal data but in what insights can be drawn from this data to facilitate better and faster decisions. This book big data and analytics is comprehensive coverage of the concepts and practice of big data, Hadoop, and analytics. From the do it Yourself steps and guidelines to set up a Hadoop cluster to the deeper understanding of concepts and ample time-tested hands-on practice exercises on the concepts learned, this one book has it all.

Buy This Book: https://amzn.to/3oXg3lf

2. Big Data Analytics, Introduction to Hadoop, Spark, and Machine-Learning

Big Data Analytics (BDA) is a rapidly evolving field that finds applications in many areas such as healthcare, medicine, advertising, marketing, and sales. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. It comprises several illustrations, sample codes, case studies, and real-life analytics of datasets such as toys, chocolates, cars, and students’ GPAs. The book will serve the interests of undergraduate and post-graduate students of computer science and engineering, information technology, and related disciplines. It will also be useful to software developers.

Salient Features:

1. Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX
2. Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics.
3. Follows a hierarchical and teach-by-example approach from elementary to advanced level.

Buy This Book: https://amzn.to/3oToQop

3. Big Data Analytics

The goal of this book is to cover foundational techniques and tools required for Big Data Analytics. It focuses on concepts, principles, and techniques applicable to any technology environment and industry and establishes a baseline that can be enhanced further by additional real-world experience. This book aims to be a ready reckoner to either a novice or a professional working in the field. Topics covered include Hadoop, MapReduce, Association Rules, Large-Scale Supervised Machine Learning, Data Streams, Clustering, NoSQL systems (Pig, Hive), and Applications including Recommendation Systems, Web and Security.

Buy This Book: https://amzn.to/2YGb7Gn

4. Big Data: How the Information Revolution Is Transforming Our Lives

Is the Brexit vote successful in big data politics or the end of democracy? Why do airlines overbook, and why do banks get it wrong so often? How does big data enable Netflix to forecast a hit, CERN to find the Higgs boson, and medics to discover if red wine really is good for you? And how are companies using big data to benefit from smart meters, use advertising that spies on you and develop the gig economy, where workers are managed by the whim of an algorithm?

The volumes of data we now access can give unparalleled abilities to make predictions, respond to customer demand and solve problems. But Big Brother’s shadow hovers over it. Though big data can set us free and enhance our lives, it has the potential to create an underclass and a totalitarian state.

With big data ever-present, you can’t afford to ignore it. Acclaimed science writer Brian Clegg – a habitual early adopter of new technology (and the owner of the second-ever copy of Windows in the UK) – brings big data to life.

Buy This Book: https://amzn.to/3iWXNog

5. Big Data, Black Book

The objective of this book is to create a new breed of versatile Big Data analysts and developers, who are thoroughly conversant with the basic and advanced analytic techniques for manipulating and analyzing data, the Big Data platform, and the business and industry requirements to be able to participate productively in Big Data projects.

Buy This Book: https://amzn.to/3BEkhSi

6. The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science

The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book.

Alex Gorelik, CTO, and founder of Waterline Data explain why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries.

1. Get a succinct introduction to data warehousing, big data, and data science
2. Learn various paths enterprises take to build a data lake
3. Explore how to build a self-service model and best practices for providing analysts access to the data
4. Use different methods for architecting your data lake
5. Discover ways to implement a data lake from experts in different industries

Buy This Book: https://amzn.to/2YLg5BB

7. Introducing Data Science: Big Data, Machine Learning, and More, Using Python Tools

Introducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience first-hand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it.

Buy This Book: https://amzn.to/2XcBlA4

8. Big Data Analytics

Big data analytics presents a comprehensive treatment of the subject for undergraduate and postgraduate students of computer science and engineering, information technology, and other related disciplines. The book has been written to cover the basics of analytics before moving to big data and its analytics. It seeks to translate the theory behind big data into principles and practices for a data analyst. Key features br>Chapter outlines and learning outcomes listed at the start of each br>Chapter illustrative discussion on big data frameworks and infrastructure algorithms for data analytics on big data frameworks and tools solved numerical examples to supplement the text practice exercises and codes for various case studies on Hadoop, R, Spark, MongoDB, storm, and Neo4j interview questions highlighted as boxed items in each br>Chapter point-wise summary at the end of each br>Chapter to enable quick revision chapter-end exercises comprising objective-type questions with answers, critical thinking questions, descriptive type questions, and numerical exercises.

Buy This Book: https://amzn.to/3AvZ1gk

9. Big Data: Principles and Best Practices of Scalable Real-Time Data Systems

This book presents Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You’ll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you’ll learn specific technologies like Hadoop, Storm, and NoSQL databases.

Buy This Book: https://amzn.to/3FS3WMD

10. Big Data Fundamentals: Concepts Drivers: Concepts, Drivers and Techniques

Big Data Science Fundamentals offers a comprehensive, easy-to-understand, and up-to-date understanding of Big Data for all business professionals and technologists. Leading enterprise technology author Thomas Erl introduces key Big Data concepts, theory, terminology, technologies, key analysis/analytics techniques, and more – all logically organized, presented in plain English, and supported by easy-to-understand diagrams and case study examples.

Features:

1. Presents vendor-neutral coverage of concepts, theory, terminology, technologies, key analysis/analytics techniques, and more.
2. Illuminates fundamental and advanced principles with hundreds of images, diagrams, and real case studies.
3. Clarifies the linkages between Big Data and existing enterprise technologies, analytics capabilities, and business intelligence systems.
4. Clear, consistent, logically organized, and up-to-date.
5. The newest title is ‘The Prentice Hall Service Technology Series’ from Thomas Erl.

Buy This Book: https://amzn.to/3lzhhkt

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

A New York Times bestseller. Longlisted for the Financial Times/Goldman Sachs Business Book of the Year Award. Since Aristotle, we have fought to understand the causes behind everything. But this ideology is fading. In the age of big data, we can crunch an incomprehensible amount of information, providing us with invaluable insights about the rather than the why. We’re just starting to reap the benefits: tracking vital signs to foresee deadly infections, predicting building fires, anticipating the best moment to buy a plane ticket, seeing inflation in real-time, and monitoring social media in order to identify trends. But there is a dark side to big data. Will it be machines, rather than people, that make the decisions? How do you regulate an algorithm? What will happen to privacy? Will individuals be punished for acts they have yet to commit? In this groundbreaking and fascinating book, two of the world’s most-respected data experts reveal the reality of a big data world and outline clear and actionable steps that will equip the reader with the tools needed for this next phase of human evolution.

Buy This Book: https://amzn.to/3mRbqXc

Here, in this article, I provided the list of Most Recommended Big Data Books for Beginners and Professional and I hope this Most Recommended Big Data Books for Beginners and Professional article will help you with your needs and you enjoy this Most Recommended Big Data Books for Beginners and Professional article.