
Optimising Network Performance Through Data Integration

Industry
Telecoms
Challenge
A major telecommunications provider was facing inefficiencies in managing its vast network infrastructure. Data was siloed across various systems, including network monitoring, customer billing, and service platforms, making it difficult to gain a unified view of network performance. This fragmentation led to delayed responses to network issues, customer dissatisfaction, and increased operational costs.
Solution
The team first integrated data from multiple sources, including network sensors, customer billing systems, and service platforms, into a single data architecture using data integration solutions. This allowed real-time data flow across systems, enabling a unified view of network performance. Data models were created to represent the network infrastructure, customer interactions, and billing information, providing a structured understanding of how data flowed through the company’s operations.
The team implemented strict data governance policies to ensure that all network data, whether generated by sensors or customer platforms, adhered to defined standards for accuracy, availability, and security. Additionally, data storage solutions, such as data lakes, were used to store large volumes of unstructured sensor data. This made it easier to retrieve and analyse historical data, while data standards ensured consistency across platforms.
With these elements in place, the telecom provider could monitor network performance in real-time through interactive dashboards, allowing them to proactively identify potential issues and optimise service delivery.
Results
Within six months of implementing this data architecture solution, the company saw a 30% reduction in network downtime, significantly improving customer satisfaction. Operational efficiency improved by 25%, as real-time insights enabled quicker responses to network issues. Additionally, the unified view of network and customer data reduced troubleshooting time by 20%, cutting down on operational costs.
Key Takeaways

Data integration provided a unified view of the network, simplifying performance monitoring and troubleshooting.

Data models ensured clear representation of network and customer relationships, aiding in quick identification of issues.

Data governance policies ensured accuracy, security, and reliability across all platforms.

Data storage solutions enabled easy access to historical data, helping optimise network performance and reduce downtime.
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