Book Image

Mastering SQL Server 2014 Data Mining

By : Amarpreet Singh Bassan, Debarchan Sarkar
Book Image

Mastering SQL Server 2014 Data Mining

By: Amarpreet Singh Bassan, Debarchan Sarkar

Overview of this book

<p>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.</p> <p>Next, you will be taken through the various classification models such as the decision tree data model, neural network model, as well as Naïve 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.</p>
Table of Contents (17 chapters)
Mastering SQL Server 2014 Data Mining
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Listing of popular databases


A data store is the most basic necessity of any application. If we are generating some data in any application, we will require a backend database for it. Various applications might entail some needs, which would require us to use some specific data sources. For example, if our host operating system is on Unix, we might go for Oracle or any of the databases that are installable on a Unix system to host our data. The following are some common enterprise data stores that are available today:

  • SQL Server

  • Oracle

  • IBM DB2

  • Sybase

  • MySQL

  • PostgreSQL

  • Teradata

  • Informix

  • Ingres

  • Amazon SimpleDB

We will now look at the tools available at our disposal to transfer the data from some (Oracle and IBM DB2) of the preceding database systems to SQL Server, as that is where our staging database is going to be. As discussed in the previous chapters, the same data in different applications might be represented in different forms; for example, an employee might be uniquely identified by an employee...