Data in telecom
telecom data: network and usage data, customer analytics and churn prediction, and privacy/regulatory constraints on rich data.
Telecom generates some of the densest, most continuous data in any industry: network signaling, CDRs, geolocation, device telemetry, and billing events at massive scale. This block builds fluency in how telecom operators structure, measure, and govern this data. You will learn the core data concepts as applied to networks and customers, then map the actual data landscape: OSS/BSS sources, network performance datasets, churn and usage metrics, and the quality benchmarks operators track. Finally, you will cover the regulatory and privacy regime specific to telecom (location data, lawful intercept, metadata retention) and the governance controls and audits needed to keep data trustworthy, compliant, and usable for analytics and AI use cases.
Ce que vous allez maîtriser
- Map the core OSS/BSS and network data sources an operator relies on and explain what each captures
- Evaluate telecom-specific data quality metrics such as CDR completeness, latency accuracy, and churn-label consistency
- Identify privacy and regulatory obligations around location, metadata, and lawful intercept data in telecom
- Design a practical data audit checklist for network and customer datasets before they feed analytics or AI models