This blog discusses the Top 10 Most Important Data Mining Books in 2020.

There is no dearth of data around us. We have been collecting data since the better part of a century and until recently we failed to understand the importance of it.

Structured and unstructured data can be both leveraged to make transforming business decisions and improve data-driven decision making.                                                               

The art and science of examining and evaluating this data is called Data Mining. It can be used to unearth patterns and relationships hidden in huge reserves of data.

Learning Data Mining is the first step to understanding any data-related job spheres. You need to learn how to extract useful data from a sea of un-amassed data.

Why are Data Mining Books important?

Data Mining books provide you a cushion to fall back on when dealing with huge volumes of incoherent data. 

They allow you to refer to a repository of Data Mining projects, theory, applications, best practices, tips and tricks etc. And, there is just one such repository- the good old books.

Data Mining books are authored by big names in the industry so that these serve as a ready reckoner when professionals need it. Next question that might boggle you- Which books to choose? To help you with this, here is a list of top 10 Data Mining books that are not in a particular order but will definitely adorn as a meaningful addition to your Data Science reading resources.

Let’s start flipping the pages….

1. Mining of Massive Datasets

Authors: Jure Leskovec, Anand Rajaraman and Jeffrey Davis Ullman

With an aim to put forth important concepts and tools to manage, manipulate and feed large data sets into databases, Mining of Massive Datasets is one of the most popular Data Mining books. The book covers overs several crucial topics like social network analysis, PageRank algorithm and recommendation system.

You can buy it here. 

Why this book?

The core focus area of this super important book is applying practical algorithms to solve key business issues related to the space. Therefore, this book includes stream processing and locality-sensitive hashing algorithms that aid in speedy processing. The algorithms and processes detailed in this book can be easily applied on your largest dataset.

2. A Programmer’s Guide to Data Mining

Author: Ron Zacharski

As the name suggests, the book focuses on Data Mining with programming’s base. It is centered around collective intelligence, Data Mining and developing recommendation systems. There are several chapters in this book like implicit ratings and item-based filtering, clustering, recommendation systems and naive Bayes etc.

You can check out the book here.

Why this book?

Enriched with different practical problems on the topics taught and following a learn-by-doing approach, this is one of the most important practical guides to own, if you wish to get hold of the basics and master the advanced topics. This means it is a perfect fit for programmers who wish to have a resource that is not just theory but a mix of practical and theoretical guide.

3. Data Science for Business: What You Need to Know About Data Mining and Data Analytic Thinking

Authors: Foster Provost and Tom Fawcett

Did you know that Data Analytics and Data Mining are connected? Well, this book establishes a relationship between these two processes- how can you think analytically and mine the data to draw fruitful insights from it. Authored by the coveted Data Science experts, this book also details the basics of Data Science.

Buy the book here.

Why this book?

This book not only focuses on theoretical concepts but the practical part of it; how can you use Data Mining Projects for the purpose of your business. Enhanced with real-life business examples, comprehending popular Data Mining techniques is easier. 

4. Introduction to Data Mining

Authors: Pang-Ning Tan, Michael Steinbach and Vipin Kumar

Hailed as one of the most popular books for introducing Data Mining, this book details topics in a balanced way- theory and practical both. While there are explicitly detailed theory chapters on pattern mining, clustering etc., it also integrates figures and examples.

You can purchase the book here.

Why this book?

One of the more celebrated Data Mining books, this book follows a structured approach- two chapters for every crucial topic; one has detailed basics to master specific techniques and the second one has intricate algorithms and concepts. Pick it now if you wish to have a step-by-step approach to learn Data Mining and Data Mining Projects.

5. Data Mining: Concepts and Techniques

Authors: Jiawei Han, Micheline Kamber, Jian Pei

Expect to get a Data Mining course content from a book? Pick up this book. You will get to read and understand every important topic related to Data Mining. Authored by two of the popular Data Mining researchers, Jiawei Han and Jian Pei, this book functions like an encyclopedia that details mining techniques and concepts and tools used in drawing insights from the data.

You can buy the book here. 

Why this book?

Apart from detailing the mining techniques and other processes of data, this book also covers specific techniques utilized in correlation for large data sets and mining continuous patterns etc. Whether you are a researcher, application developer or a business professional, this book is for you.  

6. Mining the Social Web

Author: Matthew A. Russell

Want to take up mining of social media platforms? This book details how to carry out this extremely important process; how can you also capture data from the social media apps. Mining the Social Web’s focal point is data visualization and data manipulation tools.

You can purchase the book here.

Why this book?

What not many books do, is that they don’t provide a balanced blend of theoretical and practical concepts. But Mining the Social Web includes well-explained theoretical concepts powered with practical applications of it. This book has a brief of social web landscape, use of Docker for running code in each chapter, with Jupyter Notebook as the base and understanding and contributing to the GitHub platform.

7. Data Mining: The Textbook

Author: Charu C. Aggarwal

Adopting a structured approach of starting with the basics and moving on to the advanced topics, this book is one of the most revered Data Mining books in the field. This book has all the latest information and is authored by one of the most famous Data Mining researchers. 

You can check the e-book here.

Why this book?

Apart from getting to know about Data Mining applications, you will also get to see different types of problem domains related to issues in the field. All the concepts in the book are covered in an integrated and comprehensive manner. Some of the unique topics included in this book are- social network mining, graph mining and time series; something that other books don’t include.

8. Data Mining: Practical Machine Learning Tools and Techniques

Authors: Ian H. Witten, Eibe Frank, Mark A. Hall

Studied quite a lot about the theoretical part of machine learning and now searching for a book that can present some real situations where machine learning is applied? Pick up this book as it is enriched with real-world scenarios wherein machine learning tools are used.

You can buy the book here.

Why this book?

This book has practical advice on how to implement tools and techniques in your real-world Data Mining projects. Also included are the strategies, tips and tricks to increase the efficiency of your models by altering the input or output.

9. Data Mining and Analysis: Fundamental Concepts and Algorithms

Authors: Mohammed J. Zaki and Wagner Meira JR.

Data Mining and Analysis is authored by one of the renowned researchers Mohammed J. Zaki. It is a step-by-step approach book, meaning it details on crucial topics (the basic ones) and then moves on to more complex ones. This book has all the practical and popular algorithms that are the most preferred in Data Mining projects.

Check out the book here.

Why this book?

You won’t find any algorithm superficially explained; each of the algorithms in this book is intricately detailed. With the help of this book, you can also analyze models and patterns for any type of data. You will get an integrated model of study, wherein Data Mining concepts are related to statistics and machine learning concepts and would be helpful to Data Mining projects.

10. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management

Authors: Gordon S. Linoff and Michael J.A. Berry

Dedicated to the business and marketing management, Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management puts forth case studies to relate techniques to real-life; how to apply them to your Data Mining projects. Each of the chapters has a new technique on mining data and practical and precise explanation on executing every technique.

You can purchase the book here.

Why this book?

The latest edition has revised and updated content that shows the right way to unleash techniques and methodologies to resolve business problems. This book is intended for Data Mining Specialists, business managers and marketing analysts. You will also find chapters dedicated to highly advanced topics like developing an important framework for this field. 

This is an exhaustive list that covers Data Mining books for both freshers and experienced. Now, it is up to you to decide which book you want to own. Reading Data Mining books has always been one of the easiest things to do as this way you will know what not to do and also how to apply Data Mining practices in real-life Data Mining projects. Go and grab one now!