XenonStack Recommends

AIOps Solution for Telecom Industry

Acknowledging Data Management
          Best Practices with DataOps


XenonStack White Arrow Image

AIOps Overview

Gartner first coined AIOps in 2017. AIOps for Telecom is a constituent of two terms i.e., AI (Artificial Intelligence) and Ops (Operations). Operation management is cumbersome for an organization. From customer experience to anomaly detection, all required a team of experts for handling a particular department’s operation. This leads to a considerable cost for an organization in terms of money and time. As the current era is data-driven, and it is generating with high velocity and veracity. Finding the pattern from this data (big data) using Analytics and Machine Learning is both cost and time-efficient. AIOps is a way of utilizing Big Data and Machine Learning for handling an organization’s operation with scale and efficiency and is entirely automated. It lets the concurrent use of data sources, data ingestion methods, real-time analytics, and presentation of infographics.

What drives AIOps?

Machine Learning (ML)

It is a way of mathematically learning the pattern from data without human intervention. ML can find patterns from big data in less time, and with the power of analytics, it suggests better actions.

Performance baselining

Identifying the threshold performance, gives better criteria for analyzing the performance of an event in real-time.

Anomaly detection

Real-time judgment of an unusual event prevents an organization from losses such as customer, revenue, trust, etc.

Automated root cause analysis

Finding the causality of an event and auto-generation of information concerning the context helps in finding the better remedial solution.

Predictive insights

Prediction of future behavior based on past data and auto-training on new data makes AIOps smart, efficient, and reliable.

Problems solved by AIOps Solutions

  • Shifted the reactive analytics to proactive analytics
  • Gave big data a real meaning by finding some useful insights using ML and Data Science
  • Prioritization of issues and smarter notifications
  • Finding a correlation between the events and reduce the traffic of anomalous     events
  • Most importantly, it is a one-stop solution for monitoring in real-time from data ingestion to analytics, real-time alerts, and visuals, better suggestions, etc.

AIOps Use cases

Faster root cause analysis: Faster identification of the primary cause of the problem and better troubleshooting suggestions. Earlier detection of problems: AIOps is a proactive approach for dealing with unusual situations by analyzing the expected set of patterns. Alert prioritization: Notifies those problems which can cause a significant loss during that time. Auto-noise reduction: Find the correlation between the noise (alerts) automatically and helps in faster resolution.

How does an AIOps Platform Looks

Better visibility - Captures minute changes in infrastructure at every millisecond, which helps better tracking of the problem. Full-stack monitoring - The monitoring should be a complete solution in itself from real-time data ingestion to anomaly detection. Intelligence - With the use of AI, the system automatically replicates the ability of domain experts and suggests better solutions.

AIOps Solutions in Telecom

Improving Customer Experience

Telco is a customer-centric industry. The long waits in the queue of technical support, billing dispute, updation of credentials, etc. cause a customer to switch to another carrier partner. With the introduction of chatbots for solving conflicts and use of the ticket routing algorithms has exponentially decreased the customer wait time and improves customer experience. These things happen in real-time.

Anomaly detection

Telecom is highly vulnerable to anomalies, such as identity theft, data breach, fraudulent transactions, etc. AIOps for Telecom is all set for handling such defects, trained using advanced ML algorithms on big data, and the patterns generated by these algorithms can detect the anomalies with high accuracy. The predicted anomalies are then prioritized and create a no-panic situation for the company.

Customer Segmentation

Dividing the customers into groups based on the opt services, billing information, payment type, revenue generation, etc. AIOps find such groups or clusters in real-time and gives better suggestions like buying behavior and upselling capacity of the customer. Such clusters will also lead to monetization of tailored content for the customers.

AIOps Tools

Prometheus: An open-source monitoring system fetches real-time data from HTTP metrics, and flexible query language model makes it an excellent choice for AIOps.

AIOps Solutions for Telecos

To fulfill rising expectations of modern-day customers experience, telcos need to put as much focus on customer experience as you put into other functions. But, the question here is – do you carry that expertise, experience, and resource base? AIOps is boon for every emerging telecom industry. With a decade of industry experience and having attained a credible name in the IT domain; XenonStack works as a strategic business partner for industry across telcos. Some of the top brands in the Telecom industry rely on us to look after their CX initiatives. Get in touch with us to know more.

Related blogs and Articles

RPA in Supply Chain - Reimagining Your SCM with Automation Bots

Cognitive Automation

RPA in Supply Chain - Reimagining Your SCM with Automation Bots

Introduction to RPA in Supply Chain RPA stands for Robotic Process Automation, which allows you to automate the Processes. Robotic Process Automation is a technology that works within the software and eases human efforts and hence called Software Automation. Supply Chain includes the Flow of Goods and Services between the organization and the suppliers. These terms coalesce to form RPA in...