There’s a lot of hype around the notion of “real time analytics” and, as a result, a lot of confusion around the concepts of real-time reporting and real analytics. However, real-time reporting and real analytics are not the same — nor are they interchangeable. Understanding the difference is crucial, because each serves a specific use case and therefore functions differently.
How They Differ
Real-time reporting allows you to understand what’s going on in the IT environment right now. Operational reporting systems typically use real-time reporting to do exactly as the name implies —monitor operational applications. Real-time reporting can also be found in application performance management systems, providing real-time visibility into the technical performance of a server, router, or load balancer. Both types of applications are akin to the speedometer on your car dashboard: you need to keep an eye on the apparatus to take immediate but limited corrective actions, such as easing up on the gas to reduce speed.
The purpose of real analytics, on the other hand, is to understand patterns, trends, co-relationships, outliers, and so on. Predictive analytics is a good example of real analytics in action, requiring large amounts of historical data and co-relationships in order to forecast future outcomes.
With more complex analytical methods such as real analytics, data must be extracted and stored in a separate repository built specifically for analyses. Real analytics cannot be performed using the same system that does real-time reporting, because querying huge amounts of data from an operational system would significantly degrade performance. Using an operational system for real analytics is absolutely the worst thing you can do performance-wise; before you know it, the CIO will be asking you why the operational system is, well, nonoperational. If you try to address both use cases with one tool, you’ll never be successful. Worse still, you could bring mission-critical systems to a standstill.
Reporting and Analytics in Action
Taking the car analogy further, your car dashboard has a variety of gauges to tell you your speed, RPM, temperature, and oil and fuel levels. The dashboard is your car’s equivalent to real-time reporting, with the gauges telling you how your car is operating at the moment. Alternatively, real analytics would involve taking thousands of data readings from thousands of sensors on your car, storing the information in a data lake, and then using it to support real analytics. Real analytics could analyze variations in data to help “guide internal decision processes, from better understanding and predicting customer preferences to driving design, testing, flexible production planning, and quality assurance.”
Both real-time reporting and real analytics play important roles in IT. You need both methods in order to fully understand and enhance operations, but you also need to make sure you use the right tool for the right job. If anyone claims that they are performing real analytics on an operational system, it’s quite likely they really have a separate data store to support those analytics. Knowing the difference between real-time reporting and real analytics can help start that conversation.
Learn more about the difference in this exclusive webinar comparing reporting to analytics.
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