More and more, using big data is becoming a common business practice. The logical next step is to speed up the way in which organizations acquire the data generated by their consumers, products and research. Organizations who effectively implement real-time business intelligence strategies and apply them to on-the-spot analytics programs will gain a considerable edge, distancing them from their competition.
In the case of business intelligence and data analytics, the early bird really does get the worm.
“Real-time” analytics in the literal sense is impossible because data generated from anywhere still needs to be processed and transferred over the air or via cable to its end location, whether that be a data warehouse or some other storage container. “Near-time” may be a more logical way to describe it, but for the purposes of speedy analytics which create new business insights, it doesn’t matter what we call it. In the digital age, companies need lightning fast transference of data from point A to point B or risk falling behind in their industry.
Imagine two companies. One uses a business-class, fiber-optic internet connection to process transactions. Now let’s imagine the other company still uses AOL dial-up internet. You know, the service that makes this ee-er sound over and over until finally connecting to the internet 9 minutes later. You get the point. That’s the difference today between an organization that regularly analyzes their data in real-time and one that does not. After a not-so-long period of time, the gap between the two is immeasurable.
According to a recent report by Capgemini, more than two-thirds of the companies polled believe that big data gives them an edge against their opponents. That is and will be magnified ten-fold in the near future as real-time data streaming and analysis become bigger trends. Real-time business intelligence is no longer a want, it’s a need.
Just today at CeBIT (which we foreshadowed here), Dr. John Bates claimed: “Data analysis in real-time is the alchemy of the future. It delivers big data gold bullion.”
Real-time data analytics is all about minimizing as much as humanly and technologically possible the time it takes to get data to a place where it can be dissected and provide user insights. Organizations no longer have to stand for traditional graphs and charts in their boardroom meetings once a month. Not every ounce of an organization’s big data needs to be collected in this way, but businesses benefit from certain data points being analyzed in real-time. With the coming Internet of Things boom that industry leaders have predicted, real-time data collection will soon be the new norm.
Outside of consumer products, real-time data analysis is paramount in a wide range of industries. Its applications are endless, from helping healthcare professionals provide life-saving care to assisting police across the world in preventing crime and responding to it swiftly with real-time data visualization.
From a business perspective, real-time data analysis gives businesses faster and more accurate insights, which allows them to respond to customer concerns, complaints and inquiries in a more timely manner with more accuracy. Looking at this through the scope of research and development, real-time data collection provides many benefits, including pinpointing software or hardware issues in “smart” products, giving business users better insight into what is working and what isn’t, and in the end, allowing devices to act as their own agents, thus maximizing production out of employees and returning maximum ROI. In short, businesses who operate in real-time are likely to have better, more responsive products, happier customers, and more profitability.
The success of real-time business intelligence is not in the technology we use to acquire our information, it’s how the data we possess is put to work. Waiting for data is so 1995.