vb.net barcode reader sdk Figure B-17 PowerPivot table in Microsoft Office

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Figure B-17 PowerPivot table
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Appendix B: MDX Queries for PowerPivot
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with member [Measures][Actual] as KPIValue("Product Gross Profit Margin"),format_string = "Percent" member [Measures][Target] as KPIGoal("Product Gross Profit Margin"),format_string="Percent" member [Measures][Status] as KPIStatus("Product Gross Profit Margin") member [Measures][Trend] as KPITrend("Product Gross Profit Margin") select {crossjoin({[Date][Fiscal][Fiscal Year][FY 2003], [Date][Fiscal][Fiscal Year][FY 2004]},{[Measures][Actual], [Measures][Target],[Measures][Status],[Measures][Trend]})} on columns, {[Product][Product Categories][Category]members} on rows from [Adventure Works]
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This is how you pull key performance indicators (KPIs) out of the SSAS cube It s valid MDX but doesn t look that good in a PowerPivot table It s the same problem as before, with the non-measure dimensions on the Columns axis The resulting table is shown in Figure B-18
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with member [Measures][Actual] as KPIValue("Product Gross Profit Margin"),format_string = "Percent" member [Measures][Target] as KPIGoal("Product Gross Profit Margin"),format_string="Percent" member [Measures][Status] as KPIStatus("Product Gross Profit Margin") member [Measures][Trend] as KPITrend("Product Gross Profit Margin") select {[Measures][Actual], [Measures][Target],[Measures][Status],[Measures][Trend]}
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Figure B-18 PowerPivot table
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Prac tical PowerPivot & DAX Formulas for Excel 2010
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Figure B-19 PowerPivot table
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on columns, {crossjoin({[Date][Fiscal][Fiscal Year][FY 2003], [Date][Fiscal][Fiscal Year][FY 2004]}, {[Product][Product Categories][Category]members})} on rows from [Adventure Works]
This is our last query in this appendix It fixes the previous query The resulting table is shown in Figure B-19 MDX is quite a powerful language! We have seen only a few queries in this appendix However, there may be just enough to get you started writing your own MDX queries
Appendix C
DMX Queries for PowerPivot
Prac tical PowerPivot & DAX Formulas for Excel 2010
ou may have SSAS data mining structures and data mining models You normally query these objects using Data Mining eXtensions (DMX), perhaps from SQL Server Management Studio (SSMS) or from SQL Server Reporting Services (SSRS) Although this release of PowerPivot supports the graphical design of SQL and MDX queries, it does not support the graphical design of DMX queries You can, however, write your own DMX You do so by connecting to an SSAS source and entering the DMX into the MDX Statement area of the Specify a MDX Query dialog, in the Table Import Wizard Another way is to embed your DMX query within a SQL query and import the data returned from the outer SQL query To do that, you connect to a SQL Server source and enter the SQL/DMX into the SQL Statement area of the Specify a SQL Query dialog of the Table Import Wizard Alternatively, you can query some data mining data from Excel itself for this you will need to download the data mining add-in for Excel (the data mining results are shown in an Excel worksheet when you use the Table Tools/Analyze ribbon, rather than the Data Mining ribbon), you can then import or link into the PowerPivot window from the Excel worksheet) Stand-alone DMX, or DMX embedded in SQL, works for DMX Cases, Content, Prediction, and other queries This chapter includes sample code for a few Cases, Content, and Prediction queries Key concepts queries DMX, linked servers, Cases queries, Content queries, Prediction
Why Write DMX Queries
DMX, or Data Mining eXtensions, is a standard language for extracting data from data mining models Specifically, it is the language used to query data mining structures and data mining models in an SSAS database By using DMX, you are no longer confined to SSAS imports from cubes only you can also import data from mining models You can write your own stand-alone DMX queries during data import One other way to get DMX imports working is to set up a SQL Server linked server to SSAS, and embed the DMX within a SQL query This appendix shows both approaches If you are interested in learning a bit more about DMX (in particular, DMX for SQL Server Analysis Services), refer to my book, Practical DMX Queries for Microsoft SQL Server Analysis Services 2008 (McGraw-Hill / Professional, 2010) Most of the examples here are taken from that book
Where to Create and Test DMX Queries
DMX is a standard language for querying data mining models The DMX discussed here is for SSAS The DMX used by other vendors of data mining software may differ in minor ways
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