A global company recently decided to do what many companies are doing: figure out how to turn big data into big profits. It put together a preliminary budget and a request for proposal that in effect asked vendors to take the data the company had and identify opportunities.
Three stages are commonly used to categorize an organization's maturity in their use of business intelligence and analytics technologies: Descriptive, or what happened in the past? Predictive, or what will (probably) happen in the future? Prescriptive, or what should we do to change the future?
Big data is the all the rage and getting tons of press as it has allowed manufacturers and supply chain executives to create new and compelling data-driven strategies that help them compete, innovate and capture wallet-share. Perhaps fueled in part by the likes of leading database vendors or system integrators (SIs) looking to cash in on high-dollar predictive analytic and scoring engagements, big data represents many things to many people, but one of the most pragmatic applications is mastering all the data elements used in a business infrastructure. The term commonly used for this process is master data management, or MDM.
Time-critical decisions in transportation, risk management, security, disaster response, manufacturing, and other operational domains require continuous real-time situational awareness and intelligence. Most enterprise systems do not provide this today.
From the smallest business decisions to the largest ones, risk influences all that we do. But taking a risk is not exactly like spinning a roulette wheel, where luck is the primary ingredient for success. With use of the right tools, risks can carefully be calculated, controlled and managed, greatly reducing the variable of bad luck.