Month: January 2024

Categories
IT Agility

Unleash the power of cloud modernization

Accelerate migration of complex data pipelines to modern cloud services using a holistic approach

Communications Service providers face several challenges in managing and processing massive amounts of data generated every day from Call Detail Records (CDRs), networks, and application logs from various sources. Big data platforms like Hadoop help manage, analyze, and derive insights from extensive data but performance limitations, scalability challenges, and high maintenance efforts make it a tough challenge.

Service providers must move towards a cloud-based Hadoop ecosystem to overcome these challenges. While there are different approaches to cloud migration, the serverless route provides several benefits when compared to the traditional cloud.

According to Forrester, more enterprises are frustrated with the complexities of Hadoop’s on-premise systems and want to shift to the public cloud. Serverless and Hadoop alternatives in the public cloud will gain more traction in the near future.

This insight sheds light on cloud modernization of service providers’ ML use cases to facilitate efficient handling of large volumes of ML data, real-time data analysis, and faster decision-making.

Fig: Cloud modernization approach to maximize the value of migration


According to Forrester, many enterprises are frustrated with the complexities of Hadoop’s on-premise systems and want to move to the public cloud. Serverless and Hadoop alternatives on public clouds will gain traction in the future.

Categories
Operational Excellence

Accelerating fibre rollouts by pre-empting order delays

Leverage AI/ML to forecast delays and reduce customer churn

Fibre to the Premises (FTTP) service delivery includes deploying high-speed fibre optic connections directly to the customer premises, which involves several complexities and unexpected delays in order fulfillment. These delays can lead to missed SLAs, high customer churn, and compensation liabilities for Communications service providers.

According to Forrester, “70% of customers are likely to churn if orders are delayed, and proactive information about orders are missed”. Hence, an intelligent FTTP service delivery becomes imperative for service providers in the Connectedness industry.

Leveraging an AI/ML-powered FTTP service delivery framework can help service providers predict and address order delays before they impact the business. With the predictions from the ML model, the operations team can gain a view of the expected delays, root causes, and ways to overcome them. This helps reduce operational overload and customer churn.

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Fig: Leveraging an AI-powered FTTP service delivery framework for on-time provisioning and improved customer experience


“70% of customers are likely to churn if orders get delayed, and proactive information about orders is missed”. – Forrester

Categories
Software Intensive Networks

Predicting network faults with ultimate precision using AI

Service providers ditch rule-based firefighting and embrace proactive AI to anticipate and prevent outages, saving millions and boosting customer satisfaction.

Network Operations Centers (NOCs) are pivotal for service providers in ensuring seamless connectivity and optimal performance. However, a surge in 5G, IoT, and virtualization technologies has brought unprecedented challenges. NOCs grapple with the overwhelming influx of alarms, struggling to differentiate critical issues from irrelevant ones. Manual reduction methods and rule-based approaches lead to delays and false alarms, inflating costs and hindering response efficiency.

To overcome these challenges, service providers must embrace a proactive approach, harnessing machine learning (ML) for precise prediction and resolution of network faults. Service providers can leverage ML to analyze extensive and diverse data sets, extract crucial insights and promptly implement preventative measures in real time.

Hence, adopting a network event prediction model becomes imperative to anticipate and proactively mitigate potential network failures and outages. It also enables service providers to ensure precise predictions, reduce network downtime, and cut operational expenses.

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Fig: Key steps to leverage ML model for ticket prediction
and prioritization


Leveraging ML to analyze extensive and diverse data sets, service providers can extract crucial insights and promptly implement preventative measures in real time.