Fresh and frozen data

Identifying which data is best used ‘fresh’ and which is best ‘frozen’ and retained for post analysis is a technique operators need to master. Effective exploitation of fresh and frozen data opens up opportunities for innovation and differentiation. Personalized experiences based on each individual customer’s own interests, behaviour, geography and unique circumstances should drive loyalty.”
Peter Briscoe
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What Peter Briscoe describes above is analogous to streaming of live event video versus stored video. Streaming video is used for real-time relevance, such as watching a big sporting event, whilst stored video could be used for playing back a conference at any time in the future.

B/OSS has always catered for this dichotomy of data, with network events being just one example. Network events are analysed and managed in real-time to respond to network health issues. But “frozen” network event data (ie stored over long periods of time) can be used to identify trends that then support refinements to routine maintenance procedures.

But in the context of Peter’s paragraph above, the next generation of innovative and differentiating telco services will rely on the next generation of fresh and frozen data from their B/OSS. Historically, B/OSS were unable to gather metrics such as customer’s interests, behaviours, location / geography, etc and nor could they respond to them. As this innovative new data is possible to be gathered, their fresh and frozen management and reporting techniques will also change. There could be a lot more data sets made available for streaming analytics.

Examples include opportunistic, real-time marketing and loyalty responses to location-based fresh data. Similarly, this greater granularity of collected data can also be frozen for long-term trending analysis with an individual or community perspective.

I wonder whether these unstructured data sets and queries can be accommodated by current B/OSS frameworks?

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