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Application of Analytics in Telecom Industry

  • June 27, 2023
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Meet the Author : Mr. Bharani Kumar

Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of Innodatatics Pvt Ltd and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 17 years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.

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There are presently 350,000 zeta bytes of data in the planet, and information is increasing. The correct knowledge and insight are hard to come by. McKinsey's 2013 study on telephony businesses "In recent years, the prevalence of communications access services has increased dramatically in developed nations. This market is heavily saturated, and a few numbers of networks dominate it internationally. This is a constant worry while managing clients and attempting to keep them, grow income, and decrease expenditures in order to boost productivity. There is a wealth of information available in the telecommunications sector. Analytics on telecom data offer fascinating insights, such as the ability to predict client shaking.

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What are the challenges faced by the Telecom & Technology Industry?

  • Network and repair failures resulting in dissatisfaction t of consumers.
  • Customers switching together to different service providers eventually sustainable loss.
  • The customer base is saturated, but more or less constant. Companies need to increase the typical revenue per user.
  • Present-day investigation has effects on the proper advertising channel.
  • Impacting the Survival Analytics to happen with agitated assumptions past the fragments.
  • Anticipating a huge drop in call rate.
  • Anticipating the organization's concerns that purchasers face by providing preventive arrangements.
  • Impacting the Survival Analytics to happen with agitated assumptions past the fragments.
  • How exploration will help the potential outcomes to undergo the Telecom Companies in the amplifying serious market.
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To further comprehend the applications, let's examine a problem-solving approach: to foresee network disruptions in order to maximise service availability.

Even when a downtime advisory is sent, customer discontent arises when a service is not accessible for any reason, maybe due to maintenance work. If a network outage or a system problem caused the unavailability, we may presume that this is how the customers feel. If a network breakdown cannot be detected in advance, telecom firms cannot guarantee high-quality service. There are too many network devices linking several regions across thousands of kilometres, making it difficult to forecast when one of them would break down.

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This may lead to several challenges like

  • This will lead to an increase in maintenance costs for the  frequent faults within the telecommunication network.
  • We are unable to proactively identify the vulnerable locations where there is a network outage.
  • Operational expenditure will surely increase for the replacement of the faulty equipment utilized in telecommunication.
  • Constraints in analyzing the enormous volumes of log files to extract meaningful insights to spot the problematic network component.

Solutions for the problem can be :

We can create a prediction model that can anticipate any malfunctions or failures of the network equipment, allowing for proactive monitoring. Therefore, we may utilise association rules and clustering approaches to pinpoint the regions where things keep going wrong and driving away customers. It is possible to track the number of days a network functions without any failure by running survival analytics on each cluster. To analyse the enormous data logs and spot abnormalities, mining can be done in addition to natural language processing and text.

This will have a favourable effect on our company. There will be a significant decrease in network failures and outages. Proactive initiatives can reduce the cost of maintenance. As a result, higher network dependability will contribute to happier customers. The earnings will rise as the turnover ratio falls. And last, increased network accessibility.

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2. To predict the utilization of network bandwidth to strategize the marketing & pricing plans

The Internet has become an essential commodity in one's life. Due to the burgeoning demand and uncertainties, the prediction of network bandwidth peaks has become a challenge to the network providers. This will cause an imbalance in feeding the necessities of customers by the network providers. Frequently these providers are left with different strategies regarding Marketing and Pricing plans.

We will not be able to effectively determine the peaks and troughs across the daily 24-hour period. To determine the architecture for load balancing. During peak hours the bandwidth would not support where customers may feel dissatisfied. To meet the future demands capacity planning would become uncertain. So we need to go through the detailed historical net flow data of the network account and build a model. Building a prediction model to identify the utilization of network bandwidth. A statistical model to predict the probability of customer purchasing if a discount coupon is sent as part of marketing strategies.

 

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Conclusion : 

Data analytics aids telecom companies in connecting more customers and providing more specialised services. Analytics has taken a central role in this evolving sector. The telecom business is undergoing another shift as a result of the problems posed by contemporary technology, and analytics is at the forefront of this change. Future sophisticated analytics will be able to automate decision-making, increasing operational efficiency. The best client experiences will be automatically provided by this.

Digital transformation in telecom 2023 :

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Moving ahead, maybe around 2023 the trendy Digital Transformation will shape the Telecom Industry. By concentrating on privacy and security, process automation, AI, and fast networks, making sure to reach out for future needs. But digital transformation within the telecom market goes beyond technology to processes. In 2023, the telecom industry will uninterruptedly develop new ways to bring 5G to the heap, providing the most ameliorate network for the public.  Moving ahead, maybe around 2023 the trendy Digital Transformation will shape the Telecom Industry. By concentrating on privacy and security, process automation, AI, and fast networks, making sure to reach out for future needs. But digital transformation within the telecom market goes beyond technology to processes. In 2023, the telecom industry will uninterruptedly develop new ways to bring 5G to the heap, providing the most ameliorate network for the public.

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