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Here is when it s time to go. When internal people are downsized, it s usually because they ve missed or ignored the signs that it was time to go all along the way. Reactive Signs No one is calling for your help, no matter how much you promote it, because personal agendas and politics take precedence over productivity and performance. You are constantly unable to work with department, division, and functional heads, and must deal with lower-level people who cannot commit to agreements nor provide resources. The organization is in flux, you are shuffled around, and/or you find yourself reporting to legal, administrative services, or other generic catch-alls instead of a true internal consulting function. You ve become a pair of hands called in like a plumber or electrician. That is, you don t participate in the what and why discussions for an intervention or project, but are merely told how to get something done for someone and are expected to execute. Your pay grade, status, and overall perception of others place you in an inferior position to organizational managers. Despite your past successes and proclaimed competence, external consultants are hired for any major project and you are either not considered or relegated to minor support roles. Arbitrary layoffs are instituted.
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Part II: Working with Plugins
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The Time Series algorithm predicts the future values for a series of continuous data points (for example, web traffic for the next six months given traffic history). Unlike the algorithms already presented, prediction does not require new cases on which to base the prediction, just the number of steps to extend the series into the future. Input data must contain a time key to provide the algorithm s time attribute. Time keys can be defined using date, double, or long columns. Once the algorithm has run, it generates a decision tree for each series being forecast. The decision tree defines one or more regions in the forecast and an equation for each region, which can be reviewed using the Decision Tree Viewer. For example, a node may be labeled Widget.Sales-4 < 10,000, which is interpreted as use the equation in this node when widget sales from four time-steps back is less than 10,000. Selecting a node will display the associated equation in the Mining Legend, and hovering over the node will display the equation as a tooltip. Note the Tree pull-down at the top of the viewer that enables the models for different series to be examined. Each node also displays a diamond chart whose width denotes the variance of the predicted attribute at that node. In other words, the narrower the diamond chart the more accurate the prediction. The second Time Series Viewer, labeled simply Charts, plots the actual and predicted values of the selected series over time. Choose the series to be plotted from the drop-down list in the upper-right corner of the chart. Use the Abs button to toggle between absolute (series) units and relative (percent change) values. The Show Deviations check box will add error bars to display expected variations on the predicted values, and the Prediction Steps control enables the number of predictions displayed. Drag the mouse to highlight the horizontal portion of interest and then click within the highlighted area to zoom into that region. Undo a zoom with the zoom controls on the toolbar. Because prediction is not case based, the Mining Accuracy Chart does not function for this algorithm. Instead, keep later periods out of the training data and compare predicted values against the test data s actuals.
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The Sun Fire Server family is well suited to provide high-performance computing for many types of businesses, including:
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LDAP client Figure 8.3 The dsservd process serving clients.
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While not as costly as a missing index, a more common problem is when SQL Server finds the correct rows using the nonclustered index and then has to fetch more columns from the data page a situation known as a bookmark lookup. Bookmark lookups can be devastating to performance because while the nonclustered index may have grouped the data to a few index pages, the bookmark lookup must now fetch data from numerous data pages. To compare the database bookmark lookup operation to an actual book, in a bookmark lookup you locate just what you need in the index, but 200 discreet page numbers are listed after the index. Turning to the 200 pages in the text of the book is the time-consuming bookmark lookup (refer to Figure 50-5). The bookmark lookup is physically performed by retrieving data from the data pages and joining the data with the results from the nonclustered index. In this case, it s a RID lookup operation because there s no clustered index, but it could also be from a clustered index seek or clustered index scan. To solve this bookmark lookup problem, either add the OrderDetailID to the ProductID nonclustered index so all the data required by the join is directly available from the nonclustered index, or convert the primary key to the clustered index, which would replace the RID in the nonclustered index with the clustered index keys. Both solutions enable the ProductID
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Title tag. Description meta tag. Keywords meta tag. Alt tags. Headlines and headers. Keyword-based links. Table Summary tags.
basically a "Black Box" that looks at the provided Select statement in the SelectCommand object, and automatically generates the appropriate insert, update, and delete commands and all associated Parameter objects. Listing 22-12 demonstrates using the CommandBuilder object to perform the exact same function that was performed in Listing 22-11. You can use the wizards available in Visual Studio .NET to configure your Command objects graphically. Listing 22-12: Using the CommandBuilder to Configure a DataAdapter
Part VIII: Appendixes
Scale entities
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Double-clicking a newsgroup posting brings up the entire message as a separate window.
Dynamic Range Error
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