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lacking in technicians coming from an OLTP environment. It does contain some great information on dimensional modeling, including techniques for handling common scenarios that arise when trying to represent business data in a dimensional model. It is difficult to make a universal recommendation about how to get your feet wet. One option is to develop your own cube to represent a solution to a problem. One of my favorite projects was to build a cube to analyze how disk space was being used on my computer. I have a difficult time identifying files that are duplicated in several folders, and building such a cube helped me identify where most of my space was going (I freed up about 30 percent of my disk space based on this analysis!). Another implementation could analyze server resource consumption. In fact, such a solution is available for download as a PerformancePoint sample (see Scorecards and Dashboards for your IT Department at http:/ /www.microsoft.com/bi/department/department. aspx id=tab1), so you can validate your approach. If there is a data warehouse project in development or already implemented at your company, you may be able to find a way to become a team member and learn from other practitioners with more experience. And there are courses available from the major training vendors to get you started.

so that the dialog box remains displayed until two seconds before the end of the song if the user doesn t click any of the buttons The new statements appear in boldface here:

people choose simple moving averages because it seems, well, simple For example, the 20-day simple moving average is calculated by taking an average of the last 20 days of the market s closing price and dividing by 20 So as the twenty-first day is added, the first day is dropped off Put another way, old days are dropped as new days become available It s constantly moving, which is why it s called a moving average By repeating this procedure every day, a smooth line is created that can be displayed on a chart Another popular choice, the exponential moving average, is calculated in a similar way except that it gives a little more weight (18 percent, to be exact) to the last few days If given the choice between simple or exponential, you may want to choose exponential Why First, it s more accurate And second, the simple moving average is a bit slower to respond than the exponential (Note: If you re interested in learning more about exponential moving averages, go to 12 for a list of helpful resources) Another choice you have is deciding which moving average to display on the chart If you re a short-term trader, you might use the 14-day or 20-day For others, the 50-day, 100-day, and 200-day moving averages give a very good view of market direction Keep in mind that the shorter the time period, the more signals that are generated You could think of the 20-day moving average as a quick and agile cheetah, while the 200-day moving average is as slow as a three-toed sloth

Summary

tell the application id "comappleitunes" with timeout of 1200 seconds try set three_star_songs to every track of playlist "Library" whose rating is 60 repeat with this_song in three_star_songs set song_details to "Song:" & tab & name of this_song & return & "Artist:" & tab & artist of this_song & return & "Album:" & tab & album of this_song & return & "Played:" & tab & played count of this_song & return & "Added:" & tab & date added of this_song set song_length to (duration of this_song) - 2 play this_song display dialog song_details with title "Change Rating of Three-Star Songs" buttons {"Rate As Two Stars **", "Rate As Four Stars ****", "Cancel"} giving up after song_length end repeat end try end timeout end tell

I hope you have gained some insight into the various aspects of business intelligence and learned how it differs from legacy OLTP applications. This should give you the fundamentals, so you can decide if this is something you want to pursue. I have found business intelligence projects to be some of the most rewarding in my professional career. Historically, IT projects have typically been about getting information entered into computer systems, so there is no greater reward than to see the excitement on a business user s face when they see how easy it can be to make some actionable knowledge out of years of stored data.