Service providers of all types are grappling with the operational challenges of managing the massive amounts of data, both unstructured and structured, being generated by their always-connected customer base.
Such data takes on many different formats including image, voice, message and web traffic. Moreover, machine-to-machine generated data multiples the network traffic that telcos must handle. This complicates management of network bandwidth as well as overall data management.
To add to the problem, the increasing use of content- and media-rich services is combining with a challenging business environment in which service providers need to make use of the vast amounts of data being produced by, and passing through, its network.
According to TM Forum, data has grown at a CAGR of 29% over the past five years, and is likely to grow at double-digit rates in the future. Today, there are nearly 6 billion phones in operation and over 2.5 billion of them are in Asia.
Data growth is getting stronger due to the transition from 2G networks to 3G and beyond, combined with the continued reduction in price points for smartphones and tablets.
Increasingly, customer data is being analyzed with the objective of getting business intelligence to improve customer experience and control costs -- and thus generate revenue.
As services grow and as network traffic rises, three things will become mandatory to handle all this big data. First is network analytics to address the degraded application performance due to increased network traffic in limited bandwidths.
Second is better tiered storage data management and automated data migration strategies, to lower the cost of handling all the data. And third is better metadata lifecycle management, to handle the machine-to-machine, application-generated, and human input metadata due to the increased applications and data files.