Companies are spending more on data and are incorporating analytics into their decision-making strategies to gain an edge in today's competitive market. By collecting larger pools of information and processing them faster, enterprises are looking to anticipate market trends before their counterparts catch wind of them and take action to capitalize on those projections, according to High Frequency Traders. There is vast potential in big data, but adopters must consider that faster isn't necessarily better if data quality is lacking.
Technology is accelerating the pace of the business world across industries, and particularly within the financial services sector, the source adds. Investors can tap into internal data and the hoards of content generated online everyday (around 2.5 petabytes) to make evidence-based calls about surprising correlations in real-time. However, speed can't substitute for poor quality. If information is incorrect or flawed, users may simply be making ill-advised decisions sooner.
Data quality must remain at the center of the decision-making process, the media outlet reports. For stock market traders, this means verifying data sources and checking conversions - a process that is particularly important when users are tapping international sources that have different standards.
Although we live in an era that enables companies to leverage advanced technology for number-crunching, address management remains a challenge, according to John Owens in a recent Integrated Modelling Method blog post. Owens explains that mistakes can occur at the point-of-entry because customers are still prompted to provide their contact data in an order that dates back to the 1600s, starting with names, postal addresses, towns, states, zip codes and ending with countries. Switching the order so that fields reflect an entrant's language first, and then narrow down options by the national postal system, can reduce the chances that they type in the wrong answers.
Students spotlighting big data's potential
Companies with the strongest data quality standards are often the most likely to succeed because they can identify inefficiencies and save money, reports The Knowledge@Wharton Today. As a result of these factors, data scientists are in high demand and the field is expected to be one of the most desirable throughout the 21st century.
Students at The Wharton School of the University of Pennsylvania are already studying big data's potential for predicting flight delays, anticipating the outcome of microloan financing and even projecting the final scores of sports games. One research team found that airlines stand to save billions of dollars every year if they can find a way to minimize flight delays.