Big data not better than gut instincts where there is poor data quality

After learning about big data's potential, a wide range of sectors bought into the strategy and invested significant sums in it. Marketers hoped to improve targeting efforts, retailers aimed to personalize service and financial institutions wanted to anticipate risks better. Basically, adopters were looking to minimize human error by leveraging data and the insights gleaned from them. 

In the aforementioned markets, decision makers have traditionally relied on their gut instincts - using fast, instinctive and intuitive cognition for predictions, according to a recent article by the Future of CIO. These can be highly accurate if individuals are in environments that are very stable. However, some companies are mistakenly tossing these influences out the window in favor of completely data-driven insights. The two can ideally coexist and support one another, the source explains. 

In some cases, it may actually be smarter to use intuition over data if there are quality concerns. At  the recent ISSA conference, vice president and chief information security office of RSA told the audience that big data is ineffective if it does not have an architectural strategy, multi-year funding or skilled people and the right tools to create meaningful and correct analyses, ComputerWeekly reports. Bad data can quickly corrupt information and render it meaningless or worse yet, mislead users so they make poor decisions that can have long-lasting consequences.