Faster Insights
Real-time ingestion and processing of 1M+ events/sec.
Turn your telecom data into actionable real-time intelligence. Connect all your silos, boost insights, drive 5G innovation – and drive operational transformation.
Telecom operators generate massive volumes of data every second - from RAN performance metrics to OSS/BSS logs. The problem is that much of this data is locked in silos, fragmented across legacy systems, and underutilized. Data democratization changes that by making data accessible, actionable, and valuable to everyone in your organization.
Traditional data management in telecom often leads to:
Data Swamps: With uncontrolled data lakes that are expensive and hard to use.
Siloed Systems: OSS, BSS, and network data stored in isolated platforms.
Complexity & Cost: Multiple legacy analytics tools and manual processes.
Slow Time-to-Insight: Delays in correlating events and responding to network issues.
As networks evolve and customer expectations rise, you need a smarter way to manage and leverage data.
Our Data Assurance solution, powered by Kalix DataOps, is designed specifically for telecom environments.
Key features include:
| Feature | Description |
|---|---|
| Unified Data Flows | Real-time and batch ingestion from multi-domain, multi-vendor sources. |
|
Support for Any Format |
Structured and unstructured data (PM data, logs, XML, JSON, CSV). |
| Cloud-Native & Scalable | Built on Kubernetes for elastic scaling across on-prem, cloud, or hybrid deployments. |
| 150+ Prebuilt Connectors | Plug-and-play integration with OSS/BSS, probes, CRM, and more. |
| AI-Powered Transformation | Automatic schema adaptation, anomaly detection, and enrichment. |
| End-to-End Visibility | Centralized monitoring, lineage tracking, and quality control. |
Real-time ingestion and processing of 1M+ events/sec.
Consolidate legacy tools into a single platform.
Proactive detection and resolution of network issues.
Supports automation and AI/ML use cases for predictive analytics.
Vodafone built a global data hub with Google Cloud and DataOps, enabling real-time network visibility and automation at scale.
Telia leveraged DataOps to reduce time-to-repair, improve customer satisfaction, and accelerate digitalization.
Data democratization empowers every team in your organization - from engineering to customer care - to access and act on high-quality data. By breaking down silos and enabling real-time insights, you can deliver better experiences, optimize operations, and innovate faster.
Faster decision-making: No more bottlenecks waiting for IT reports.
Data democratization is the practice of making data accessible, understandable, and usable to everyone in an organization, not just data scientists or IT. So that people within an organization or business can make informed decisions without gatekeepers.
Accelerate AI Adoption with Clean, Unified, Real-Time Data
If you are to capitalize successful from the promised AI transformation – such as predictive maintenance and automated network optimization – your data needs to be ready. Fragmented data, silos, inconsistent formats and legacy systems all create barriers to AI success. Our solutions enable you to get your data ready for AI.
Modernize Your Data Backbone to Power Real Time AI and Automation
Our solution integrates optimized data movement and DataOps processing to extract, transform and load your data into efficient pipelines – ready for cross-domain analytics, automation and AI.
Visit our Knowledge Center and stay up to date on Industry trends and more.
Achieving e2e-insights requires seamless ingestion, unification, and correlation of data from many sources. Read about data ingestion with AI in telecom
The Telecom Industry is facing a deep transformation. Read about the CSP status, as well as the drivers for transformation. Download here
Watch this live session on-demand, and explore how telecom can transition from GenAI adoption to true business transformation. Access webinar here
Discover how our Data Assurance solution can help you unlock the full potential of your data.