A major Middle Eastern mobile operator was facing significant challenges in managing and processing the vast amounts of data generated from its network infrastructure and customer base. With millions of subscribers and a constantly growing demand for data services, the operator struggled to process and act on real-time data, particularly in areas like network monitoring, customer analytics, and billing operations.
Their existing infrastructure was largely batch-based, leading to significant delays in processing critical data such as call records, data usage, customer behavior, and fraud detection. This resulted in:
The operator needed a real-time data streaming solution that was scalable, fault-tolerant, and could integrate with their existing systems. After partnering with Wizuda and evaluating various technologies, the decision was made to implement Apache Kafka as the core platform for processing and distributing real-time data across their network.
The operator managed an extensive network infrastructure, which included a significant number of cell towers and network devices generating logs and metrics around the clock. Previously, network performance issues, such as service outages or dropped calls, were only identified after the fact through batch-processed logs.
One of the biggest challenges the operator faced was providing real-time updates to customers’ data, call, and text usage, especially for prepaid subscribers. Their legacy system processed billing data in batches, leading to discrepancies between actual usage and the available balance shown to customers, often frustrating them and leading to support calls.
Fraudulent activities, such as unauthorized use of SIM cards or SIM box fraud, where international calls are routed through local numbers to avoid high tariffs, were growing concerns for the mobile operator. The fraud detection system needed to analyze call patterns and behavior across millions of transactions, but the batch processing of call records caused significant delays in identifying suspicious activities.
The mobile operator had customer data spread across multiple systems, such as CRM, billing, and support platforms, making it difficult to gain a holistic view of each customer’s journey. Departments like marketing and customer support were working with fragmented data, leading to inefficiencies and a lack of personalized service.
With the growing trend toward 5G and IoT services, the mobile operator knew that their data volume would increase exponentially in the coming years. The company needed a scalable platform that could handle future demands without requiring significant rearchitecting.
By implementing Apache Kafka, Wizuda enabled the mobile operator to successfully transform its data architecture to meet the challenges of real-time data processing. Kafka provided the foundation for scalable, real-time data pipelines that improved network reliability, enhanced customer experiences, and enabled proactive fraud detection. The operator was not only able to meet current demands but also positioned itself for future growth with Kafka’s scalable and fault-tolerant architecture.
