Traditionally, the concept of BIG DATA has been used to describe the mountains of user data collected by many large enterprises. (Think retail, Telco.) These companies learn what they can from the data and often resell it to marketing companies as a side business. What marketer wouldn’t want access to stats on buying behavior, television viewing and phone usage habits, demographics, and geolocation?
But the increasing popularity of SaaS systems and the growing significance of web applications in our daily lives has given rise to a new set of Big Data collected from machines, not people. Why is this an important trend? It’s the application. Web and mobile apps are now indispensable. And to improve them — to make them even more useful and fast by learning about how users interact with them — companies like New Relic provide monitoring systems and collect “Big Data” about application performance.
But what about the “application performance big data problem” we’ve read about? Aren’t we collecting too much data across numerous tools with no real way to correlate and make sense of it? Maybe. But if you have a single system that monitors the application itself, real user metrics and server infrastructure performance, and then analyzes it for you, you’re well on your way to understanding most of what you need to know about your application environment. Another advantage of a pure SaaS system is that New Relic can aggregate performance metrics and give back useful data that helps companies understand their own app performance, that of their peers and tech companies as a whole. (See the App Speed Index, State of the Stack, and Browser Wars reports for example.)
As a major collector of app performance Big Data, (literally the largest application performance monitoring systems we know of!) we did a little number crunching to see just what we’re talking about when it comes to our app performance Big Data.
To see how we can help you manage the performance of your application, sign up for your free New Relic account today.