“Big data is currently at the peak of the hype curve, and while service providers can collect more data than ever from many different sources they don’t always know what to do with it. Valuable insights are often missed simply because they aren’t asking the right questions of the right data to generate useful intelligence.”
Patrick Tan on TelecomAsia.
Big data is often used for identifying customer experience. The interesting part of “customer experience” is that it often relates to the user’s experience when consuming content rather than the traditional services that are monitored by OSS.
Let’s say you’re using a smart-phone to access a video served by a website on the Internet. The end-to-end customer experience relies on multiple technologies ranging from web server, content management system, database server, operating system on the phone, the phone itself, etc as well as the network over which the content is carried.
OSS traditionally manage and monitor the performance of component parts (eg CPU utilisation on servers) or uptime on devices on the network rather than the end-to-end experience.
Is your OSS asking questions that relate to individual components or end-to-end experience?
Do you have access to data from every layer in the end-to-end experience stack or only some? What method do you use to tie the stacks together? Synthetic actions that mimic a user experience (eg a web-site’s response time), amalgamation of stats from the different layers using big data, or perhaps some other clever approach?