Big data has already made its mark across industries. Insurance companies are using it to reduce risks and anticipate claims, banks are tapping analytics to determine which individuals will pose the greatest risks for loans and retailers are investing in it to anticipate when product demands will peak so they can procure adequate supplies.
The growing demand for big data analytics has put a premium on individuals who can look at data sets and spot needles in haystacks. For instance, Andrew Schwartz, data scientist and co-founder of Lattice Engines, told The Boston Globe that he helped a casino optimize its slot machines after learning that people are more likely to continue playing if they hear others winning, regardless of the size of the prizes.
When companies have great
data quality, they can put together a complete picture from seemingly random pieces of information as a way to reduce costs and enhance performance. For the casino, that meant lower payouts and more play.
Inspired by the success of early adopters, more companies are planning to invest in big data throughout 2013, according to FormTek. However, their progress is contingent upon devising a plan ahead of time with measurable goals and data quality tools that will ensure information is accurate and consistent.