While the end case study outlines an array of potential benefits of data visualisation for both the consumer and commercial entity, it also becomes apparent that a failure to conduct a data cleanse is likely to result in negative impacts upon a data visualisation project. One key problem for a project which does not conduct a sufficiently rigorous data cleanse is the prospect of information overload. As the case study highlights, organisations have access to a vast array of data however, the point of a data visualisation project is not to simply bombard the user with endless reams of data but instead to present the user with the data which is going to allow for the greatest improvements to decision making be these consumer or corporate based decisions (Miller and Han, 2009).
Further project problems which may be the result of a lack of a data cleanse of scrub may be the consideration that such a project may deliver poor or inaccurate results. One of the main points of a data visualisation project is to provide an accurate view of consumer behaviours as seen in the statistical evidence as opposed to what qualitative research reports. However, such information as is to be provided through a data visualisation project may only be assumed to fill this missing gap where the data is sufficiently complete and accurate (Miller and Han, 2009). Again one may consider that a key aspect in ensuring the accuracy and completeness of the results of a data visualisation system is the implementation of a high quality data cleansing exercise in the first place which verifies the quality of the data to be used in the final project.
Miller, H, J, Han, J. (2009). Geographic data mining and knowledge discovery. 2nd ed. Florida: CRC Press.