By Piyush Agarwal, SE Leader, Cloudera
Over the past decade, there has been a notable surge in the adoption of digital transformation among businesses. This trend is particularly evident in the Indian telecom industry, where the utilization of data and data-driven automation has played a pivotal role in driving business growth. This includes optimizing network operations, enhancing customer support, and exploring new market opportunities. As telcos aim to strike a balance between cost-cutting and innovation, the adoption of a modern data architecture (MDA) emerges as a game-changer, enabling efficient data management, integration, and governance.
In India, where the telecom sector is fiercely competitive, embracing an MDA is key to sustaining growth and success. For instance, cloud computing adoption in India has been on the rise across various industries. This has enabled telcos to promptly diagnose issues, enhance operational efficiency, and deliver personalized products, ultimately transforming the customer experience.
A modern data architecture enables real-time visibility into telecom networks, helping telcos promptly diagnose issues, enhance operational efficiency, and deliver personalized products, transforming the customer experience. But the adoption of the architecture is a challenging process due to various factors such as the integration of the complex legacy system of telcos, the creation of data silos that disables the unified view of the data and hinder data-driven decision-making and the need for a scalable and secured solution for the adoption.
Addressing these challenges require careful planning, strong leadership, and collaboration across different teams within the telco organization. To embrace the benefits, telcos should take the following steps to adopt a modern data architecture by minimizing disruption, controlling for risk, and positioning themselves for growth—
Modernize data flows– According to the recent IDC Financial Insights report, the cloud is increasingly seen as the underlying architecture for Indian business applications By adopting a modern, distributed data architecture, telcos can eliminate silos, reduce expenditures, and improve productivity. A modern, distributed data architecture supports a hybrid data platform for managingdata across on-premises and multi-cloud environments. A seasoned hybrid data service provider helps businesses to operationalize data analytics and AI solutions for improved data-driven decision-making and operational efficiency.
Offload data from legacy, on-premises analytic platforms and appliances– On-premises analytic systems can often cost more than cloud-based alternatives. By adopting a modern data architecture, telcos can offload excess data to inexpensive virtualized storage. According to Forrester’s ‘The State Of Cloud In India, 2023’ report, about 73 per cent of Indian enterprise cloud decision-makers use at least two cloud deployment models.
Reduce customer complaints– By using predictive models and machine learning (ML), telcos can reach out to affected customers facing disruptions, suggesting workarounds or offering credits, refunds, and incentives. By using ML to analyze data from call centers, chat logs, and social media and provide a tailored customer experience. Analytics tools can be utilized to perform sentiment analysis on customer feedback and complaints.
Automate Data Governance– Data governance is crucial for ensuring data accuracy, quality, integrity, and privacy, as well as for promoting trust in data. However, the activity of millions of connected 5G devices, for instance, will present an unprecedented challenge to data governance. Telcos will need to use device data to enhance their networks, transform their operations, and improve the customer experience. To achieve this, they must integrate this data with sensitive information from customer accounts.
According to McKinsey & Company, the telecom industry can predict and reduce churn by 15% through advanced data analytics. Navigating this challenge requires robust data governance controls that permit a holistic view of data, track how data is used and by whom, allow for role-based access, and enable authorized users to access data easily and securely.
Reduce the Frequency, and severity of network outages– Telcos can predict and prevent outages, optimize coverage, detect threats, and improve the user experience by correlating network performance with behavioral and hygiene data. For instance, predictive modeling can be used to set thresholds for events like network element failure, where managers get alerted automatically.
Data will continue to grow
A recent Internet and Mobile Association of India (IAMAI) report, ‘Internet in India’, estimated that there are a total of 692 million active Internet users in India. That number is expected to hit 900 million internet users by 2025, which will generate an enormous amount of data. In India, businesses are looking to harness the full potential of their data. Studies by IBM show that 99% of organizations in India are using some form of hybrid cloud architecture, making it critical to unlock value from this data no matter where it resides.
For telcos, it becomes imperative to reinvent their data management and analytics strategy in this era of data-driven business. A multi-function, open, end-to-end platform makes it possible to generate the enterprise data insights needed to drive business value across multiple key use cases. Having these end-to-end data lifecycle components integrated into a unified and secured platform empowers telcos to effectively address their most compelling use cases, driving the customer experience, guiding network optimization, delivering operational analytics, and empowering them to expand their business offerings.