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The sales order has to be one of the most standard and most downtrodden examples in the history of data modeling textbooks. Surely you don t need any advanced techniques to find the functional dependencies for this example; you ve seen it so often that you could build the relevant tables in your sleep. And that makes this an ideal example scenario for this chapter. Using a simple and recognizable example enables

Upsides Highlights of my practice include being part of the consulting team that helped Jack Welch at General Electric create a culture based on speed, simplicity, and self-con dence and participating in similar efforts at JP Morgan, Sears, Disney, and General Motors I had the good fortune to work with consultants and academics who were

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you to check my questions and the answers provided by the fictitious domain expert, and to see for yourself that the procedure of asking questions and drawing conclusions outlined in this chapter will indeed result in the correct data model a statement you d have to take for granted if I d chosen to use a more complex example In real life, you won t follow all steps exactly as I outline them here, but instead immediately conclude functional dependencies in case you feel confident that you re sufficiently familiar with the domain, and use the detailed procedure in situations where you re in doubt or have no idea at all.

The drag coefficientscan then be computedwith Eq (2 l) Becausewe are performing operations vectors,we must include periodsprior to the operators: on element-by-element

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But for illustration purposes, I ll presume that I (as the data modeler) am completely unfamiliar with the domain of sales orders, so I can t assume anything, but have to ask the domain expert everything I need to know So let s focus on WeTrade, Inc, a fictitious trading company, where I m supposed to model the database for their sales orders I ve already acquired a sample order confirmation form (figure 2), which I used to determine that the data model would include the attributes OrderNo, CustomerName, CustomerID, Product, Qty, Price, TotalPrice, and OrderTotal The procedure for finding all functional dependencies is easier to perform if you first lay out all attributes in a simple tabular format, with the attribute names as column headers and some sample data below them.

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You need to start with at least one row of data, and you re well advised to keep the number of rows low I chose to use the contents of figure 2 as my starting data, so this table will look like table 1 You ll probably have noted that this table is already in first normal form That should be the starting point If at this stage there are multivalued attributes (for instance, an attribute Customer with contents of Northwind/12 and AdventureWorks/ 15) or repeating groups (for instance, attributes Product1, Product2, Product3, Qty1, Qty2, Qty3, TotalPrice1, TotalPrice2, and TotalPrice3), get rid of those first before you start the procedure to find functional dependencies..

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Use MATLAB's incerpl fr"rnction fit this datawith (a) linear interpolation, nearest (b) to neighbor(c) cubic splinewith not-a-knotend conditionsand (d) piecewise cubic Hermite interpolation Solution (a) The datacan be entered, with linearinterpolation, plottedwith the fit and following commands: >> r - [0 20 40 56 68 B0 34 95 t04 110]; >> v = l0 2A 20 38 B0 80 100 10A \25 7251;

The implementation of maintenance plans (MPs) has changed over time. From SQL Server 6.5 to 2000, an MP was executed by sqlmaint.exe through a SQL Server Agent (Agent) job. As of SQL Server 2005, an MP is a SQL Server Integration Service (SSIS) package, executed by an Agent job. You create a plan using SQL Server Management Studio (SSMS) and rightclicking the Maintenance Plans folder under the Management folder. You can use either a wizard or a trimmed-down version of the SSIS package Designer, available inside SSMS. For beginners, I recommend using the wizard, and, as you get more comfortable using MPs, you can dive into the Designer. The SSIS package is saved directly to the msdb database (not out in the filesystem as a .dtsx file) along with some metadata in the msdb database, indicating that the plan exists. This metadata allows SSMS to list your plans in the Maintenance Plans folder, where you can right-click and edit them. If you choose to schedule the plan, which you typically will want to do, then one or more Agent jobs will be created.

= finspace ( O, 110 ) ; >> tt = incerpl(t,v,r-t); >> vl >> plot (t,',' o', tt,vl)

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