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Poor data quality limits analytics

Rachel Wheeler Archive
There are several common problems that plague analytics projects. SQL Server Pro contributor Brian Knight recently compared the situation to the gold rush saying that many companies are prospecting for insight, but only a few will strike it rich. He noted that persistent issues including frequently poor data quality derail these efforts.

According to Knight, there are issues with storing and maintaining information at every company, linked to a general lack of awareness. He noted that, in terms of technical problems, data quality is the most common impediment to business intelligence success. Information silos that do not work together often lead to disagreement.

There are many ways to counter disparities between records. Knight suggested that companies can create specific areas in servers to act as data quality staging grounds. This would be where the cleansing processes run, making sure different recording methods agree.

The recent InformationWeek Reports survey regarding business intelligence for 2013 confirmed that cleansing data is very much on tech users' minds. The study found poor information quality to be the number one factor limiting business intelligence success. On the whole, the report found ample evidence that analytics will be a huge factor in the coming year.