Is Big data the big elephant for service assurance?

As telecom providers onboard new services and customers, network and service assurance becomes more complex and more difficult to manage. One key reason for this is the poor quality of the network and service assurance data, which often suffers from:

  • A lack of priorities
  • A lack of service context and customer context
  • And too much irrelevant data

The industry has made various and regular attempts to address this issue, yet without any real breakthrough. As a result, alarm correlation efforts often fail due to the impossible nature of rule maintenance. Similarly, initiatives focusing on inventory system lookup – to help build context – drastically fail due to incorrect and incomplete inventory data.

Don’t pin all your hopes on Big data

The industry has now turned to Big data in the hope that it will help solve the assurance data problem. The general belief seems to be that we can throw even more low-quality data into a Big data platform and magically get the answers we need. However, Big data scientists concur that this simply isn’t possible. Thus, for the data issues mentioned above there is simply no silver bullet and to think Big data is the easy answer boils down to a disproportionate belief in the technology or an over zealous product vendor over-selling their capabilities.

And why is this? Successful Big data projects have two preconditions:

  • Highly relevant, high-quality data must be available – quantity is not quality
  • Clear definition of questions to answer – there’s no magic wand for all questions

Service-focused assurance is a way forward

At Data Ductus, we strive to take a more service-focused approach. In the solutions that we deliver with our partner Netrounds, for instance, we provide high-quality data at the service layer. Focusing on data quality at the source in this way, enables you to answer specific questions such as:

  • Does the service work at turn-up?
  • What is the network loss, latency and jitter?
  • What is the Mean Opinion Score (MOS) score for Structured Insulated Panels (SIP) calls.

For more information about this approach, see our joint white paper on small data versus Big data at:

If you are interested in discussing these topics with us, get in touch.