Telecom, Media & Aviation
Telecom operators generate call and network records by the billion, media companies collect web, social and streaming data by the terabyte a day, and airlines record every inspection and incident across a fleet. All three run operations that cannot wait for an overnight batch — and many still run on BI environments designed for monthly reporting and maintained by teams stretched thin.
The work is to build platforms that absorb volume and velocity using native cloud services rather than proprietary tools, to bring finance, HR and operational reporting onto a modern, self-service-ready environment, and to leave behind a team that can develop and distribute analytics itself.
Where data pays back in network operators
Terabytes a day
Web, social, streaming and network data at a volume and variety legacy ETL cannot process — long reporting cycles and high maintenance as a result.
Legacy BI and manual reporting
Financial and HR reporting done by hand on an old BI environment, with a team not equipped to develop analytics and a business slow to adopt it.
Operational incidents seen too late
Safety, quality and service incidents captured in operational systems but not visible to management until long after the fact.
No 360° view of the customer
Subscriber and audience touch-points spread across systems, with no predictive or advanced-analytics capability on top.
Services for network operators
- Data Engineering & Warehousing Big-data pipelines on cloud services — object storage, distributed processing, cloud warehouses — automated in code with no proprietary tools; near-real-time capture where operations run on it.
- Business Intelligence & Self-Service BI environments upgraded for self-service; finance and HR KPIs on the ERP; incident reporting with search and root-cause exploration.
- Data & AI Strategy A clear analytics roadmap and the training that lifts adoption and maturity across IT and the business.
- Integration & Migration Move analytics environments to the cloud and retire legacy ETL and scheduling.
- Managed Analytics Ongoing run and enhancement where the operator prefers not to build the team.
Outcomes
What changes
- A complete analytics environment on the cloud, with cost savings from retiring proprietary tools.
- Real-time analytics and 360-degree customer analysis with automated error recovery.
- A future-ready BI environment with a trained team and rising adoption.
- Operational incidents visible to management in near real time.
Questions we're asked in network operators
Yes. We collect high-variety data into cloud object storage, process it with distributed frameworks and serve it from a cloud warehouse — automated in code, with no proprietary tools and automated error recovery.
With an upgrade to a self-service-ready environment and a roadmap, then training for the IT team and the business so adoption follows the technology.
Minutes, not hours: change capture from the operational system into the reporting platform in under fifteen minutes is a standard design target.
Once the platform is in place, yes — customer 360, churn and demand models are natural next steps, and the platform is designed so they can be added without re-engineering.