Many businesses feel that the benefits of big data have been oversold, with little actionable insight yielded from massive clusters crunching on terabytes of event logs or other semi-structured data. These pioneers have learned that business value of such excercises depends only partly on the tools used and a great deal on data sources along with clearly identified business objectives.
A new category known as software analytics rests on a simple proposition: The software on which your business runs can provide a wealth of data to determine how your business is performing. In this week's New Tech Forum, Lew Cirne, founder and CEO of New Relic -- which provides application performance management as a service -- explains how his new software analytics offering can deliver the right insight at the right time to both management and IT. -- Paul Venezia
Software is everywhere -- what can it tell you?
Virtually every company is now a software company, no matter what the industry. The intersection of SaaS, cloud, big data, and the consumerization of IT has changed the way all companies operate. Applications now sit at the heart of our lives, helping us stay connected throughout the day and serving as the connection point with our favorite brands. It's no secret that these apps generate massive volumes of data -- data that contains invaluable business insight, if you know how to unlock it.
This app revolution is powering a massive shift away from IT-centric, infrastructure-focused, cost-cutting priorities to software-centric, line-of-business value focused on business growth. No longer will organizations be dominated by monolithic data centers with artificial divisions between application developers and IT operations. SaaS, mobile, and cloud-distributed applications are lowering costs and offering dynamic and flexible capabilities that are highly responsive to rapidly changing competitive needs.
Enter software analytics
The tools we use have been generating increasing amounts of valuable data, but they haven't been easy to work with, and the data hasn't been directly aligned with the business. A new industry category, software analytics, is changing all that.
Software analytics presents a new way to look at the power of software, combining infrastructure management, operational intelligence, application performance management, real-time analytics platforms, and business optimization and analytics applications. All of these categories center on recorded events that should be measured and analyzed as a whole to understand different aspects of your business and the underlying apps and infrastructure. But all this is siloed data unless there is a real-time analytics platform that can analyze across data categories to open up valuable views of how businesses can work smarter and connect better with customers.
Here's how software analytics works and why it matters:
- Software analytics refers to the events and metrics that can be collected from inside modern software, at the code level, revealing critical details not just about how the software is performing, but also about the aggregated behavior of users and customers. Intelligent agents inserted into the code gather event-driven metrics in real time from live production software, which essentially records how customers are interacting with your business.
- Collecting data directly from source applications allows the people who build and run modern software to better understand its performance, health, user experience, and business value.
- Event-driven metrics reveal where and how your business is faring by tracking your customer interactions, measuring everything from how your customers are using (or not using) features on your Web application to the items they add or abandon in online shopping carts.
- Using SaaS and cloud-based architectures, billions of these event metrics can be automatically collected centrally, without companies having to build out big data analysis infrastructures themselves.
- Easy, ultrafast, and ad hoc querying allows companies to drill deep into complex business questions with multiple, iterative queries.
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