What is common to a banker who intends to determine which of her customers are at a greater risk of account-takeover fraud and a retailer intending to reach out to a prospective customer who happens to be in the vicinity of the retail outlet? The answer lies in big data analytics. Big data is the buzz word today. The old idea of data residing in rows, columns, reports and purchase transactions is passé. The form of data has evolved and now, it also originates from tweets, videos, click streams, sensors used to gather climate information, posts to social media sites, cell phone GPS signals and various other unstructured sources.
IBM estimates that every day we generate 2.5 quintillion bytes (1018 bytes or 1000 petabytes) of data leading to creation in last two years itself, of 90% of all data available. Eric Schmidt, the CEO of Google, took everyone by surprise in a conference in 2010 when he declared that we create as much data in two days now as we did from the dawn of civilization until 2003. Therefore, it is called as big data. Doug Laney of Gartner, Inc. defined big data as “high-volume, -velocity and –variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” It promises to companies not just information, but insight. It provides an opportunity to unravel the mysteries in the past, present and future when explored using tools e.g. modeling, experimental design, prediction, optimization and simulation. For an organization, it translates into more objective yet speedy decision-making. Big data is already influencing the way companies approach customers. The outcomes are evident in the form of new concepts floating around as well as cases of profitable execution. For example, location based advertising (LBA) is rapidly gaining traction. LBA has gained significance due to use of social media and its features e.g. location. LBA allows focused marketing communication with specific reference to location. With rise in m-savvy customers and availability of technology to track, LBA is being pitched as one of the top high-value mobile services to achieve mass adoption. Fraud detection is another area where big data is turning out to be of help. Ruchi Verma and SR Mani of Infosys reported a case wherein GE Consumer & Industrial Home Services Division saved about US $5.1 million in the first year of using SAS to detect fraudulent claims by unscrupulous service providers from within the organization.
Big data and analytics may not be inexpensive, but it is definitely proving to be cost-effective by resulting into insightful decisions. The companies which believe in engineering the future are gaining new insight through big data analytics and thereby, adding value to their processes and outputs vis-à-vis their stakeholders.
-Dr. Manit Mishra