DEC 2018 - JAN 2019CIOAPPLICATIONSEUROPE.COM9Lies,Damn Lies, and Data Visualization1. Do the data themselves present a clear picture or is a visualization needed? If you are trying to show that the cost of IT services goes up as the number of users increases, you may not need a fancy visualization. Avoid gilding the lily and stick to listing the few relevant facts if that is the point you are trying to make. Not everything needs to be in a chart to be meaningful.2. Does the visualization give the essence of the data? Nobody wants to reverse-engineer a graphic in order to understand the underlying point. If your goal is to highlight your aging infrastructure, only bring in other elements, such as location or hardware brand, when it is a meaningful attribute of the case for change.3. Does this depiction of the facts leave anything open to interpretation? When your goal is to share information and not make a specific case, then let your data visualization speak what it will. In cases where you are trying to make a point and support it with data, be sure your visualization makes it obvious. Avoid falling in love with your own work. Double and triple check that the visualization illustrating the data has a clear message and that the truth it conveys is not just your pet view. Do not expect the consumer of the data to be able to make nuanced evaluation of the picture you have painted. Paint your picture decisively and with style!4. Could you create a visualization with the same data that supports a very different viewpoint? The link between the underlying data and the visualization should be clear and it should be one-way. Do not try to convince with a pretty picture alone... the data themselves should be very compelling; the visualization only makes the point more clear.IT remains an art. No organization has the same setup as any other. Technology practitioners must be both artists and scientists. For data visualization, this is doubly needed. Do not assume that the graph auto-generated by your tool actually sends the message you want to convey. Think carefully about the need for the visualization, the essence of the data supporting it, how it could be interpreted and whether there are alternative conclusions that the data supports. You have license to be creative, which is necessary for you to successfully convey your truth through data visualization. While a picture is worth a thousand words, a chart is worth even more in data points
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