Some big data users ignoring quality

Big data has changed the way companies engage with their internal information. Many would argue that these alterations have been for the best, with analytics projects now able to take on complicated subjects that they could not breach before. There is a dark side to improved data collection and harnessing, however. Information Management contributor Jim Harris recently stated that many companies are blundering heedlessly in pursuit of big data, taking in more of it but not keeping up with quality measures and standards.

Management being ignored

CIOs are still learning the big data ropes. This has been manifested in an honest excitement for any and all processes that can yield a long list of figures. Harris, adopting the physical fitness metaphor of data expert Daragh O'Brien, explained that companies need their data programs to become lean and fit, but adding more information is simply making them fatter. In this vision of the enterprise situation, data quality and management efforts are the fitness programs that can help companies get in shape.

Data quality in the big data era, according to Harris, is a delicate balance between monitoring input, making sure every piece of information is useful and serves a purpose and rigorously applying standards to that information. While he conceded that many things about information management have changed in recent years, from how much data cleansing is enough to the very nature of the analytics problems designed to extract value, he stood by the assessment that some data quality tools are still relevant and necessary.

Harris explained that while the tendency to add more data is very much present, numerous experts have already weighed in with the steadying opinion that having the right data is better than taking in unnecessary figures. Firms may belatedly learn that they already have access to all the data they need, rendering advanced collection efforts largely unnecessary.

Everyone's job

Finding a place in the corporate structure for data management is an important consideration at a modern, information-rich organization. According to a recent TechTarget report, there is no one best place to locate the data quality apparatus. The source stated that the best practice with regard to data cleansing efforts involves arming employees with knowledge of data management standards and practices and the tools and incentives to uphold them during their everyday encounters with the company's information reserves.