Big Data is no longer new. Actually, it’s not even as new as it might appear. While the term itself might have only gained a foothold in recent years, driven by the emergence of technologies either designed to harness it or reliant on it to be impactful, the existence of such data itself, - (albeit theretofore unused), - has been a constant in the telecoms industry almost from the start.
Billing systems? Always been in the Big Data business, so we’re told. CEM companies? Big Data is the raw material whose input is required to deliver end-user value so they’re Big Data players too! Analytics solutions? Obviously. What, after all, is Big Data about if not analyzing the haystack to find the needles?
The question for telcos in the first evolving and now maturing Big Data age is how to identify the right areas and then where to find solutions that execute nascent Big Data strategies.
With that in mind, let’s identify some simple truths:
1. Big Data is the information created when actions or events are recorded in volume; customer business actions and/or network operational events, for instance. Therefore, Big Data is sourced from raw usage and other records (CDRs, IPDRs, log files, probe capture, etc.), generated when something is driven by an end-user action.
2. These records need to be extracted from their source components - operation or business/network elements or various sub-types of enterprise software - and then unified and exploited (put to use). In raw form and in raw numbers/volumes, the records that make up Big Data are inefficient and expensive for handling by any downstream system. They’re certainly big and they’re certainly data, but they’re not useable “Big Data” at this raw stage. So telcos need to modify core data as well as put it to work.
3. Once the data has been identified, extracted and processed (in real-time) the now usable Big Data can feed “actions” that turn it into Useful Data rather than simply Big. Useful Data is the next stage on the journey for telcos. It can drive CEM, loyalty, analytics, marketing and other end-outcomes that improve a customer’s relationship with the service provider.
This is a simplified picture but accept it at a high level and we’re getting to an understanding of what the term Big Data really encompasses for telcos. A Big Data strategy is an enterprise scale data processing and “re-cycling” program that might have a variety of different end-goals (for example, enhanced Customer Loyalty and reduced churn) all of which are mission-critical to the CSP’s financial health.
Solutions such as Evolving Systems’ loyalty technology platform can analyze Big Data feeds for marketing purposes and detect interesting behavioral patterns. The resulting actions can be used to drive, unlock and monetize network-sourced data in new and attractive (to the customer) ways.
Many mobile operators are not using Big Data strategically because they remain unable to manage it. CSPs must deploy solutions that allow this to happen. To give an idea of what's involved, a typical tier 2 operator in Europe might generate
d around 200 million records a day on the BSS side; a tier 1 operator in the U.S. might be dealing with 6 or 7 billion records a day for BSS. That’s a gold-mine of information. IF it can be tapped then harnessed to drive a more effective future relationship with the customer base, Big Data will finally realize its potential.