How much time does your company have to spare? In most cases, the answer is “none”, with most businesses looking for anything that can help streamline processes and in turn increase ROI. Data analytics — a powerful tool in the quest to make sense of massive information volume — often gets overlooked as a candidate for automation. In large measure, sheer power is the biggest concern for C-suite executives and IT professionals: What happens if the system gets it wrong? But in a world now powered by cloud computing services and tech-savvy consumers, however, the question needs to change — what tasks can analytics automation take off IT and end-user plates to help them get it right?
According to a recent Wall Street Journal article, the automation in analytics is quickly moving past the “nice to have” stage and into an era of necessity. Thomas Davenport’s article points to seemingly simple actions — for example, determining the price of airline tickets based — that would be time-consuming for a human but are simple for automated tools with full access to company data. With ticket purchasers now demanding this information in real-time, automation becomes the easy answer.
Or consider the evolving role of analytics by utility providers. As noted by Energy Biz, for the bulk of the 20th century, electric utility infrastructure operated without the benefit of tools which could report on the state of specific assets or measure spikes in usage. Now, automated tools are making it possible for utility companies to act in real-time even during powerful storms or in the aftermath of environmental disasters. In addition, these new tools include customer-facing solutions which provide instant reports about power usage and potential savings. In other words, automation equals improved efficiency.
Security is another critical arena for automation. Consider that data complexity has already moved beyond the human capacity to handle. The result? Sixty-seven percent of companies are told about internal data breaches by outside agencies, and the average attacker spends 229 days in a corporate network before being detected. This means that despite the benefits companies glean from descriptive, prescriptive and predictive analytics, systems are still at risk thanks to the sheer volume of data and the speed at which it is produced.
So what’s the solution in a time-strapped world? Automation. And not just any automation — not simply automating a few processes or “as needed,” but automation that stretches from the application to the end-user level and can detect even the slightest change in network behavior. By incorporating comprehensive comparative behavior analysis, along with taking responsibility for this implementation off the plates of local IT, it’s possible to see what’s happening before attackers have a chance to set up shop and before outside agencies step in to point out critical flaws.
It’s simple: Analytics tools are now powerful, user-friendly and critical in day-to-day operations. The next step in a maturing market is automation that stretches end-to-end, helping you get a handle on big data — and avoid bigger problems.