计科专业设计外文文献翻译sql2005毕设论文.doc

毕业设计(论文) 外文文献翻译 专业 理学院 学生姓名 班级 计科092 学号 200901051 指导教师 英文原文 Introduction to Data Mining Abstract: Microsoft? SQL Server? 2005 provides an integrated environment for creating and working with data mining models. This?tutorial uses four scenarios, targeted?mailing,?forecasting,?market?basket, and?sequence?clustering, to demonstrate how to use the mining model algorithms, mining model viewers, and data mining tools?that are included in this release of SQL Server. Introduction The data mining tutorial is designed to walk you through the process of creating data mining models in Microsoft SQL Server 2005. The data mining algorithms and tools in SQL Server 2005 make it easy to build a comprehensive solution for a variety of projects, including market basket analysis, forecasting analysis, and targeted mailing analysis. The scenarios for these solutions are explained in greater detail later in the tutorial. The most visible components in SQL Server 2005 are the workspaces that you use to create and work with data mining models. The online analytical processing (OLAP) and data mining tools are consolidated into two working environments: Business Intelligence Development Studio and SQL Server Management Studio. Using Business Intelligence Development Studio, you can develop an Analysis Services project disconnected from the server. When the project is ready, you can deploy it to the server. You can also work directly against the server. The main function of SQL Server Management Studio is to manage the server. Each environment is described in more detail later in this introduction. For more information on choosing between the two environments, see Choosing Between SQL Server Management Studio and Business Intelligence Development Studio in SQL Server Books Online. All of the data mining tools exist in the data mining editor. Using the editor you can manage mining models, create new models, view models, compare models, and create predictions based o