All companies that focus on collecting large volumes of data - especially for-profit corporations that have competing businesses nipping at their heels - have a vested interest in maintaining data quality. Having knowledge is good, but making sure it's accurate knowledge is even better, and there are all too many companies that fall short in this area.
Perhaps the most important aspect of quality is not something mundane as spelling or capitalization or formatting, but rather, it's a pursuit that demands constant vigilance. According to Information Management, the essential value to look out for is timeliness.
Competitive businesses today don't just care about having the best data - they also want the fastest data. Imagine a retail organization, for instance, that's hoping to use analytics for measuring what's become of people's shopping habits. This is an interesting topic, but what happens if the company relies on sales data from six months or a year ago? Their findings will be outdated, and they may waste time and money on marketing initiatives that don't matter.
Data quality expert Jim Harris, according to the news source, believes that a shift has taken place. People used to curate their data according to computability theory - in other words, "Produce correct answers - quickly if possible." They've since embraced complexity theory instead, which states "Produce timely answers - correctly if possible." Timeliness is now king.
"More space is being created to deliver more data within the same, or smaller, time frames," Harris explained. "Space isn't the final frontier, time is. Due to the increasing demand for real-time data-driven decisions, timeliness is the most important dimension of data quality."
None of this is to say that other aspects of quality don't matter. Formatting and business relevance are still important factors. But in today's high-tech environment, data quality is greatly diminished without speed.