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Taking a closer look at this dashboard, we see that it has very focused metrics It presents volume and pricing data for housing sales trends The space has been used very well For example, the check boxes for navigation on the line chart type have been incorporated into the display of the chart type The titles are clear and direct and don t take up a lot of space; Housing Sales Trends comprises only about 5 percent of the total space available There is some scrolling in the lower-left report but that is very limited since in this case we are scrolling only 12 months at a time and therefore it will always be the same level of scrolling, which would not be the case if the rows were controlled by something like types of homes where the total number of rows might expand and contract The yearly average sale price report is well positioned and consistent We see that the metrics have been structured to between four and six depending on whether you define the use of years as another metric This dashboard is direct and focused Monthly Sales Price and Yearly Average Sales Price with additional historic perspective based on information from 2005 through 2007, then details by Month for 2008 Again, in this case the color is used to identify the primary metrics top two charts and then it draws your eyes to the lower two reports I would have used a different background color so that the bottom two reports are not as minimized as they actually are due to the darker black against lighter black background The coloring that is going on is very basic, no highlights or fading activities and the scaling is clear and consistent I believe that there should also be a third button at the top of this dashboard Price, Volume, and Price/Volume Analysis since we can gather much more information if we integrated these two sets of metrics into an overall analysis but that would have depended on the report requirements and this would be second-guessing the development requirements In that case, I would have offered an additional prototype dashboard with the additional button to draw the business user s attention to this possibility Since we have about 4 5 metrics on each of the screens it would be reasonable to have an additional button for a total of 12 15 metrics for this dashboard You can also see that there are only four boxes in front of the business analysts This immediately gets the analyst what they need with no assumptions or guessing required by the analyst This is a good, solid, well-designed dashboard and takes into account the needs of the business analyst and also of the BI system Now, let s take the lessons learned from the previous examples and apply them to another dashboard and dig into the details of the actual architecture in the WAD in the process Remember, you first need to have your sources of data correctly formatted and ready to go for the different chart types that you will be presenting So, you should have already decided on the chart types, reached consensus on the KPIs, and gotten the data sourced appropriately defined to make the configuration process easier and more focused on the design and display than on the data Nothing is as frustrating as developing the entire dashboard and then executing it only to find that the information that you expected to see is not there In this case, I m going to adjust the format to scale into the thousands to help clear some space on the screen next to the Y-axis The next illustration shows the same chart and chart type with different scaling You can see that it s a bit clearer with the scaling turned on, but remember that you have to identify the change in the scaling factor somewhere in your titles Also, remember that scaling might affect other charts in your dashboard, but as long as all the amounts are going to be scalable, then making the adjustment to the display is safe
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