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5G Perspective

“You scratch my back, I scratch yours!” – Advanced data analytics and 5G technology

Thinking of a successful 5G deployment without customised advanced analytics or thinking of a real advanced data analytics/artificial intelligence implementation without 5G is like “a blind man in a dark room looking for a black cat that isn’t there!”

“You scratch my back, I scratch yours” is an old tactic, used both, for good and for the not-so-good. Advanced analytics and 5G cellular deployment seem to be using the same – for the good, though. With 5G rolled out in select cities and massive coverage planned in the near future, it is impossible to think of successful 5G rollout without intelligent advanced analytics backbone to manage the network and vice versa.

Why successful 5G implementation needs Advanced Data Analytics. 5G technology brings many benefits but has constraints as well:

  • Small cell size;
  • Large number of devices that each cell shall support; and
  • A variety of device types, etc.

5G networks are inherently extremely complex with multi-layered functions (typically, virtual), RAN assets (both, virtual and physical), and thus need efficient spectrum usage, given the distributed computing nodes. It becomes critical, therefore, for network planning and optimization (NPO) function to decide where and how much to scale specific functions and application services. This uses advanced machine learning algorithms – not standard machine learning algorithms but customised algorithms – depending on the use case and the context. Real-time network analytics thus is critical for a flexible 5G network deployment with both aspects – roll-out and operational complexities in mind. Thus, thinking of a true 5G network with an operations and business support system (OSS/BSS) that is not supported by an advanced analytics backbone, integrated and embedded into their toolset, is out of question.

Till now, analytics was an afterthought for cellular operators, a good-to-have – advanced analytics in 5G shall be an architect and a key differentiator of a successful 5G implementation – a forethought, a must-have item on the checklist. Ask any successful 5G implementation expert and (s)he shall swear by the dire need for an advanced network analytics backbone for 5G to give desired results.

In that sense, network analysis algorithm, that has built-in capabilities of:

  • An early warning system;
  • A self-correcting fault identification and rectification module;
  • Intelligent load balancing; and
  • Alternative branching, becomes a must.

It is clear that such network analysis algorithms drive efficiencies and, therefore, are the secret sauce. Has anyone ever heard of a secret sauce that is available to all? And that is why the key differentiator of one 5G network from another is this secret sauce – a customized advance analytics network analysis algorithm (AANAA).

Meaningful advanced data analytics needs 5G availability? Just as communication technology is progressing at the speed of light – second generation to fifth generation with age of each generation reducing drastically (and significant strides about sixth generation already making news) – advanced analytics industry is no different.

The industry made shifts from masses to classes (from broad segments such as demographic segments to hyper-personalized, hyper-localized segmentation), from reactionary approach to pro-active approach (rather than reacting to customer behavior, adding stimuli that can drive the customer behavior), from speed over accuracy to speed with accuracy, from descriptive/predictive or pre­scriptive analytics to decision analytics. The biggest shift that continues to unfold is from business intelligence to data analytics to artificial intelligence and now, to decision intelligence.

‘The biggest shift that continues to unfold is from Business Intelligence to Data Analytics to Artificial Intelligence and now, to Decision Intelligence.’

The industry is always striving hard to move the bar up on both dimensions – speed on one axis and accuracy on the other – implying that the decisions need to be real-time (not near-real-time) with a very small margin of error.

In technical terms, the same error margin that was acceptable till a few months back make the predictive model completely redundant today. To reduce the error implies reading much more signal from data part of which was earlier ignored as noise. And this implies more complex equations that have many more variables, measured to a much finer degree now. This implies a need for more variables; and a need for finer measurement of most variables and both, imply data density to increase manifolds. Increased data density, in turn, needs broader communication channels and the ability to communicate fast and securely on these channels.

In simpler terms, to arrive at such a complex and fast decision making, one needs humungous amounts of data (that flows from multiple sensors) at the speed of light (read, ultralow latency), coupled with immense computing power.

Thus, there are two critical criteria – ability of the communication network to support a very large number of devices and the ability to communicate the same with near-negligible latency. And 5G networks fill exactly that gap.

Thus, thinking of an ad­vanced analytics imple­mentation with­out a 5G network and vice versa is like a blind man in a dark room looking for a black cat that isn’t there! We foresee very exciting, unheard of times ahead in terms of usability and speed of transmission of

*With inputs from Gaurav Bhaskar & Pabitra Chakraborty, Partners, Facts ‘n’ Data*

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