Big data, AI and Machine Learning

Leading Innovation for Big Data Telecoms

Download the Datasheet

Big Data, AI and Machine Learning: Leading the Innovation in telecoms

Big data itelecoms offers a big oppprtunity. Over the past eighteen months in particular, Big data, Artificial Intelligence (AI) and Machine Learning (ML) have moved to the forefront of the technology conversation in the telecoms and many other industries. For marketers at Communications Service Providers these advances urgently need to be fully understood particularly from the perspective of the innovative Use Cases they could potentially drive if their valued is to be unlocked and they are to have the desired impact on their businesses. 

In 2020 there are around 7.7 billion active mobile broadband subscriptions worldwide, meaning more and more complex unstructured big data is being created vy telecoms, but needs to be mined effectively. It is becoming imperative to gain insights from these mammoth volumes of data if CSPs want to lead their markets by delivering better customer services, identifying needs and offering solutions based on effectively utilizing what initially is little more than a Big Data repository.

Understanding application of AI and ML in telecom

Download the Datasheet

Achieve superior decision making with Machine Learning and AI

To leverage the power of big data telecoms  must urgently start using Big Data and Machine Learning technologies to simplify and derive ‘usable’ (meaningful) information from new data points to achieve superior decision making that positively impacts revenues and customer satisfaction.  Machine Learning opens new horizons for sets of information, creating models that can add a new dimension to decision-making. The iterative aspect of Machine Learning is particularly important because as models are exposed to new data, they can independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results.

At present, Big Data is typically understood in the context of four characteristics; the four ‘Vs’:

  1. Volume: How much data is there
  2. Velocity: How fast data is processed
  3. Variety: The various types of data
  4.  Veracity: accuracy of data

To these, a fifth characteristic can be added – Value.

However, it can be misleading and overly simplistic to do see telecom big data only this way. As a result, the CSP business manager today faces this question: At its current scale, should my organization be using Machine Learning and Big Data analytics to better understand and utilize our data repository?  To learn how to assess the correct answer to this and more about the opportunities that AI and ML afford in the area of maximising the value of Big Data, download our datasheet by clicking the link above or click here to contact Evolving systems and schedule a conversation immediately.

 

Download the Datasheet 

 

Big Data Telecoms
 

Monestise the power of data

CSPs must urgently start using Big Data and Machine Learning technologies to simplify and derive ‘usable’ (meaningful) information from new data points to achieve superior decision making that positively impacts revenues and customer satisfaction.

Download the datasheet to find out how.