BI 与数据挖掘有何关系？
我对如何将 BI 与数据挖掘联系起来有点困惑。 BI是否可以被称为数据挖掘的某种表现形式？
像 Microsoft Analysis Services 这样的 BI 工具与像 Weka 这样的数据挖掘工具有什么不同？
我想BI更多地涉及数据的报告和分析，其中数据经过某种聚合并以立方体的形式表示，但数据挖掘也涉及不同的算法来执行聚类，不是吗？
有什么指点吗？
干杯
I'm a little confused on how to connect BI with data mining. Can BI be termed as some kind of a manifestation of data mining?
How different is a BI tool like Microsoft Analysis Services from a data mining tool like Weka?
I guess BI involves more of reporting and analysis of data, where in the data undergoes some kind of aggregation and is represented in the form of cubes, but data mining also involves different algorithms to perform clustering, no?
Any pointers?
cheers
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BI Small 正在生成详细报告（今天的销售列表）。 涉及的数学很少，可能是计算行数和销售额总和。 您可以在此处看到名为“BI”的报告工具，
BI 媒介正在生成一个指标（该季度的利润率）。 这只是简单的代数，但由于数据量巨大，频繁生成它是一个挑战。 这是立方体和olap的世界。
BI大是做数学建模的。 这可能是从线性回归到统计模型的任何东西，凡是你能想到的。 这里的关键是模型使用大量数据。 真正的统计学家以贬义的方式使用“数据挖掘”一词，因为未经统计学使用培训的人可能会挖掘数据，直到发现虚假的相关性。 你的数据集越大，你就越有可能发现偶然的关系，而不是现实中真正存在的关系。
因为 BI 的客户是业务经理，而不是博士生、微软等供应商。 通过向我们提供黑盒“数据挖掘”工具来简化它，其中许多工具与您在 SAS 等中找到的工具相同。
我认为 BI 一词将所有这些应用程序联系在一起的唯一一点是，它们都在使用大量数据来做出业务决策。
BI small is generating a detail report (list of today's sales). Very little math involved, maybe counting rows and summing sales. This is where you see reporting tools called "BI"
BI medium is generating a metric (profit margin for the quarter). It's just simple algebra, but producing it on a frequent basis is a challenge on account of the sheer amount of data. This is the world of cubes and olap.
BI large is doing mathematical modeling. This may be anything from linear regression to statistics models, you name it. The key here is the models are using large quantities of data. Real statisticians use the phrase "data mining" in a derogatory sense because people untrained in the use of statistics are likely to mine the data until they find a spurious correlation. The bigger your data set the more likely you are to find relationships due to chance instead of there really being such a relationship in reality.
Because the customer for BI are line of business managers, not PhD grad students, vendors like Microsoft et al. have dumbed it down by providing us with black box "Data Mining" tools, many are the same as what you'd find in SAS and the like.
The only thing I see connecting all of these applications of the phrase BI is that they all are using large quantities of data to make a business decision.
要回答您的一般性问题“商业智能是数据挖掘的一种表现形式”，实际上是相反的。
从一般定义来看，BI 是使用公司的数据来了解市场状况并做出决策。 因此，正如 MatthewMartin 所说，它可以像 SSRS 报告一样简单，也可以像实时决策支持/人工智能系统一样复杂。
数据挖掘是商业智能的一个方面，因为数据挖掘可以使用实现聚类、神经网络等算法的工具来对大量数据进行知识发现和预测。
To answer your general question "Is Business Intelligence a manifestation of data mining", it's actually the other way around.
BI is, in a general definition, using your firm's data to understand your market conditions and make decisions. So, as MatthewMartin said, it can be as simple as an SSRS repport or as complex as a real-time decision support/AI system.
Data Mining is an aspect of BI, in that Data Mining can be used on massive amounts of data for knowledge discovery and predicition using tools that implement algorithms such as clustering, neural networks, etc.