Mastering SQL Server 2014 Data Mining

Amarpreet Singh Bassan, Debarchan Sarkar

  • 出版商: Packt Publishing
  • 出版日期: 2014-12-29
  • 售價: $1,740
  • 貴賓價: 9.5$1,653
  • 語言: 英文
  • 頁數: 386
  • 裝訂: Paperback
  • ISBN: 184968894X
  • ISBN-13: 9781849688949
  • 相關分類: MSSQLSQLData-mining 資料探勘
  • 下單後立即進貨 (約3~4週)


Master selecting, applying, and deploying data mining models to build powerful predictive analysis frameworks

About This Book

  • Understand the different phases of data mining, along with the tools used at each stage
  • Explore the different data mining algorithms in depth
  • Become an expert in optimizing algorithms and situation-based modeling

Who This Book Is For

If you are a developer who is working on data mining for large companies and would like to enhance your knowledge of SQL Server Data Mining Suite, this book is for you. Whether you are brand new to data mining or are a seasoned expert, you will be able to master the skills needed to build a data mining solution.

What You Will Learn

  • Get an overview of the data mining life cycle
  • Understand the intricacies of SQL Server BI Suite with the help of a practical example
  • Collate data from diverse data sources and build a data warehouse
  • Gain in-depth knowledge about the various data mining models such as classification, segmentation, association, and more
  • Perform data mining using Big Data and Excel add-ins
  • Work on real-world data and gain insights into it using various data mining algorithms
  • Fine tune data mining models
  • Troubleshoot problems encountered during data mining activities performed in this book

In Detail

Whether you are new to data mining or are a seasoned expert, this book will provide you with the skills you need to successfully create, customize, and work with Microsoft Data Mining Suite. Starting with the basics, this book will cover how to clean the data, design the problem, and choose a data mining model that will give you the most accurate prediction.

Next, you will be taken through the various classification models such as the decision tree data model, neural network model, as well as Naive Bayes model. Following this, you'll learn about the clustering and association algorithms, along with the sequencing and regression algorithms, and understand the data mining expressions associated with each algorithm. With ample screenshots that offer a step-by-step account of how to build a data mining solution, this book will ensure your success with this cutting-edge data mining system.