As businesses and individuals move their information from paper files to digital storage, the volume of data in the world has exploded. With this increase comes plenty of data quality maintenance woes, including deduplication and the need to update files with the most recent information. Many organizations have pushed these issues to the side, but they constitute a pressing problem that should not be ignored.

In an interview with IT Business Edge, data expert Jim Harris notes that it's human nature to be reactive rather than proactive, particularly when it comes to data quality. "It's very hard to make anyone proactive until something bad happens," he says. "I don't believe anyone can be proactive without first being reactive. The business usually doesn't care about data quality until they're hit with a negative experience that was caused by bad data quality."

Harris explains that a negative consequence of poor data quality is sometimes enough to stir businesses to action. That said, it is clearly preferable to get your organization to tackle the issue of dirty or unreliable data before it creates a major problem. It can be challenging enough to get a database cleansing or other data governance initiative underway without facing resistance from the top leaders in your organization, however.

Data quality a foundation to business intelligence

In order to convince your manager, supervisors and, eventually, the business executives that it is worthwhile to invest in adopting data management solutions and developing programs, you will need to present hard evidence for the financial consequences of low-quality information. As the InformationWeek 2012 Business Intelligence and Information Management Survey found, many companies think they will be able to achieve vast performance improvements while reducing costs if they are able to derive business intelligence from data analytics.

Data quality advocates can point out to their corporate leaders that analysis is useless if the raw data on which it is based is of low quality or is out of date. The InformationWeek researchers note that business intelligence is intertwined with information management (and its components of data quality and information integration). Out of those responding to the survey, 46 percent said data quality issues were creating a barrier for companies that wanted to adopt business intelligence and analytics products.