Alex Campbell, "Data Mining and Analytics: Ultimate Guide to the Basics of Data Mining, Analytics and Metrics"
English | 2020 | ASIN : B08KBGJMJK | 89 pages | EPUB | 2 MB
English | 2020 | ASIN : B08KBGJMJK | 89 pages | EPUB | 2 MB
Are you curious about data mining and analytics? Have you ever wondered how the world is filled with so much data and what is it used for? Do you wonder how companies use data to improve their revenue and steer themselves toward the path of success? Would you like to know why data is a new currency and companies invest so much to extract, store, and process data? Do you want to know how businesses leverage data to make millions of dollars in revenue? All of this can be achieved through data mining and analytics. If you are curious to know the answers to all these questions, this is the right book for you.
This book will break down the terms data and mining for you so you can understand the concepts individually and then as a whole. If you have been looking to launch yourself into the world of data mining and data analytics, this book will serve as the perfect launchpad. The book will introduce you to all the concepts of data mining and analytics in a very tailored manner. It doesn’t matter if you are a beginner in the field of data or a veteran; you will have something important to take away from this book.
The tools and techniques described will teach you how data mining is used by organizations to steer themselves to success. This book will take you through:
An overview of data mining and the need for data mining today
Comparisons between data mining and data science
The tasks and issues in data mining
The terminologies used in data mining
The data mining query language
Classification, prediction, and cluster analysis in data mining
This book has been tailored for you to understand data mining and analytics. There are step-by-step guides with code syntaxes so that you can understand various data mining techniques. If you’re looking for the ultimate guide in mining, analytics and metrics