Preface

What is Data Mining?

According to the Gartner Group,

Data mining is the process of discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques.

Today, there are a variety of terms used to describe this process, including analytics, predictive analytics, big data, machine learning, and knowledge discovery in databases. But these terms all share in common the objective of mining actionable nuggets of knowledge from large data sets. We shall therefore use the term data mining to represent this process throughout this text.

Why is This Book Needed?

Humans are inundated with data in most fields. Unfortunately, these valuable data, which cost firms millions to collect and collate, are languishing in warehouses and repositories. The problem is that there are not enough trained human analysts available who are skilled at translating all of these data into knowledge, and thence up the taxonomy tree into wisdom. This is why this book is needed.

The McKinsey Global Institute reports:1

There will be a shortage of talent necessary for organizations to take advantage of big data. A significant constraint on realizing value from big data will be a shortage of talent, particularly of people with deep expertise in statistics and machine learning, and the managers and analysts who know how to operate companies by using insights ...

Get Discovering Knowledge in Data: An Introduction to Data Mining, 2nd Edition now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.