LIEN 发表于 2025-3-25 07:05:09
http://reply.papertrans.cn/87/8603/860296/860296_21.pngtransdermal 发表于 2025-3-25 09:44:48
Finance Use Case: Ranking Functions,Ranking functions, when applied to financial data, can produce interesting and valuable information for analysts or portfolio managers. This information is used to predict future trading patterns based on historical patterns. A properly managed portfolio based on solid analytical data and analysis will generate profits (hopefully).NOTCH 发表于 2025-3-25 13:28:44
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http://reply.papertrans.cn/87/8603/860296/860296_24.pngLIEN 发表于 2025-3-25 23:49:17
Plant Use Case: Analytical Functions,We are going to add a couple of new tools to our toolkit in this chapter. We will take a quick look at Report Builder and also Analysis Services’ multidimensional cubes.RODE 发表于 2025-3-26 00:11:28
http://reply.papertrans.cn/87/8603/860296/860296_26.pngLATER 发表于 2025-3-26 07:52:20
Summary, Conclusions, and Next Steps,Congratulations! This is our last chapter. Let’s wrap things up by summarizing what we learned and also looking at the tools in our toolkit and where to get them. I might even tell you how to create the databases and load them too! We will also discuss how to set up the folders for storing code and also the physical database files.FATAL 发表于 2025-3-26 11:27:51
Angelo BobakIs your one--stop shop to get started with statistical data analysis and data mining using TSQL.Provides modifiable templates to use for your unique applications.Gives just enough theory to introduce原告 发表于 2025-3-26 13:35:20
Finance Use Case: Aggregate Functions,s available to us to analyze a stock trading scenario. We will dedicate one chapter to each category of functions. Each function will be used in a query. We will examine the results by looking at the output and, then in most cases, copying the output to a Microsoft Excel spreadsheet so we can generate a graph or two to visualize the results.烦忧 发表于 2025-3-26 17:52:52
Finance Use Case: Analytical Functions,ce analysis, but we will also take a look at a few strategies that involve variations of the queries, like from . to reporting table–based queries to using memory-enhanced tables to see which scheme yields better performance.