By Lynn Langit, Kevin S. Goff, Davide Mauri, Sahil Malik, John Welch
Get the end-to-end guideline you want to layout, increase, and installation more suitable facts integration, reporting, and research ideas utilizing SQL Server 2008—whether you’re new to company intelligence (BI) programming or a pro professional. With real-world examples and insights from knowledgeable group, you’ll grasp the ideas, instruments, and methods for construction suggestions that carry intelligence—and company value—exactly the place clients wish it.Discover easy methods to: deal with the improvement existence cycle and construct a BI workforce Dig into SQL Server research providers, Integration prone, and Reporting prone Navigate the enterprise Intelligence improvement Studio (BIDS) Write queries that rank, type, and drill down on revenues facts improve extract, rework, and cargo (ETL) options upload a resource code keep an eye on process support safe applications for deployment through encryption and credentials Use MDX and DMX question Designers to construct studies in response to OLAP cubes and knowledge mining versions Create and enforce customized items utilizing .NET code View stories in Microsoft place of work Excel® and place of work SharePoint® Serverook
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Additional info for Smart Business Intelligence Solutions with Microsoft SQL Server 2008 (PRO-Developer)
Another scenario for which data mining is frequently used is one where your business requirements include the need to predict one or more future target values in a dataset. An example of this would be the rate of sale—that is, the number of items predicted to be sold over a certain rate of time. We explore the data mining support included in SQL Server 2008 in greater detail in Chapter 6, “Understanding SSAS in SSMS and SQL Server Profiler,” in the context of logical modeling. We also cover it in several subsequent chapters dedicated to implementing solutions that use data mining.
However, limits in the product stack are not what determines this type of design, rather, it is determined by OLAP modeler or developer preferences. Cubes As described earlier in the chapter, a BI cube is a data structure used by classic data warehousing products (including SQL Server 2008) in place of many relational tables. Rather than containing tables with rows and columns, cubes consist of dimensions and measures (or facts). Cubes can also contain data that is pre-aggregated (usually summed) rather than included as individual items (or rows).
Sources for this data can include Microsoft Access databases, Excel spreadsheets, and so forth. It is also common to include text data (often from mainframes). This data is sometimes made available as XML. This XML might or might not include schema and mapping information. If complex XML processing is part of your requirements, you can elect to use BizTalk Server to facilitate flexible mapping and loading of this XML data. Chapter 1 Business Intelligence Basics 23 You might be thinking at this point, “Wow, that’s a big list!