Introduction to Data Mining
Introduction to Data Mining
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DOI：
10.1007/978-1-4302-0248-6_11
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发表时间：
2019-04
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影响因子：
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通讯作者：
Chet Langin
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作者：
Chet Langin
在本章中，我们将探索SSAS中包含的用于数据挖掘解决方案的强大工具。开始时，您可以将数据挖掘视为BI解决方案的一个极好的“增值”。虽然SSAS 2000包含两种数据挖掘算法，但我的客户中很少有人真正实现它们，因为对数据挖掘算法的深入了解并不是SQL Server专业人员的典型属性，而这种知识水平是使用SSAS 2000实现数据挖掘所必需的。与此2005版本中的SSAS OLAP多维数据集一样，Microsoft也做出了一致的努力来提高SSAS 2005中数据挖掘的可用性，部分方法是包括大量易于使用的向导。这些向导包含一致的、非常有据可查的对话框。然而，数据挖掘是一个复杂的主题，重要的是要理解本章是对这个主题的介绍。
In this chapter, we’ll explore the incredibly powerful tools included with SSAS for use in data mining solutions. You can begin by thinking of data mining as a terrific “value add” to your BI solution. Although SSAS 2000 included two data mining algorithms, very few of my clients actually implemented them because deep knowledge about data mining algorithms had not been a typical attribute of SQL Server professionals, and that level of knowledge was necessary to implement data mining using SSAS 2000. As with SSAS OLAP cubes in this 2005 release, Microsoft has made a concerted effort to improve the usability of data mining in SSAS 2005, in part by including a large number of easy-to-use wizards. These wizards contain consistently and remarkably well-documented dialog boxes. However, data mining is a complex topic, and it’s important to understand that this chapter is an introduction to this topic.