Case
Big data to boost mobile data services
Challenge
Telecommunication service providers depend on mini-grids to generate a network coverage that encompasses even the remotest areas. In Myanmar, XYZ’s service provision suffered greatly because of its dependence on five discrete power systems to supply energy to their mini-grids. XYZ’s NOC, as a result, had to monitor five isolated information sources also inducing high CAPEX/OPEX to maintain five individual software platforms.
With the rise in data usage attributable to a billion users having hopped onto the internet since 2013, rationalizing the delivery of telecommunication services through mini-grid systems to end-users is imperative now, more than ever.
Solutions
Neo
A fully integrated RMS platform based on Bigdata that runs on the cloud and works in conjunction with all the energy systems in the network. The tool allows teams to operate through a single platform while automating all the flows.
Functions
- Providing advanced analytics powered by Hadoop and BI tools.
- Benefitting from predictive modelling capabilities using Machine learning algorithms for better XYZ(how does it help).
Results
Neo – Functions
- Greatly diminishing OPEX with zero IT intervention from client-side by virtue of being based on a full turnkey model.
- Providing different protocols like SNMP, REST API, HTTPS interface, SSL over TCP/IP by the system for controllers to transfer data and offering northbound adapters.
Numbers
- Telenor, MPT, Ooredoo & Mytel sites are monitored through this platform
- 100% sites report data and alarms on a secure real-time interface
- 1000+ sites connected on a real-time basis that submit data every minute/5 min interval
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