Our RAN.ai Platform is the cornerstone of our portfolio for Telecom Big Data and Analytics Solutions, however its capabilities extend to other sectors. It is a platform consisting of data–driven modules offering insights to Mobile Network Operators (MNOs) with respect to:
GIS module / GEOANALYTICS engine
The scope of this module is to deliver significant information to both executives and engineers in the Telecom sector for various KPIs related to network performance. It offers advanced predictive (trending) analytics and reporting on top of geolocated big data, KPIs (e.g., Throughput, Quality, Coverage, Data usage per CA/band/ARFCN, etc.) and advanced ML-based mechanisms for analyzing areas based on selected Coverage/Quality KPIs. All the above geospatial analytics are offered in different abstraction and detail levels (i.e., municipalities and prefectures, smaller spatial bins, lines, polygons, etc.), depending on the business role (Executive vs. Engineer).
This GIS module is also offered as a standalone product for other sectors -beyond the Telecom Industry- that explores big data attached to a unique location (latitude, longitude coordinates) and time/ timeframe. It delivers advanced analytics on top of these data and displays them in a geographical context along with corresponding geospatial analytics for different abstraction levels, as well as user roles and/or preferences.
TRAFFIC PREDICTIVE ENGINE
The Traffic Predictive Engine was designed to give insights related to Voice and Data traffic predictions, a challenging task for the MNOs. Furthermore, the QoS/QoE can be impacted heavily by the proper predictions of the network traffic projection.
Based on time series decomposition and auto-regressive models the engine aims at understanding for example which areas’ network traffic will increase and by how much, which areas will experience traffic stagnation or de-growth, and which RATs and carriers will absorb the additional traffic can have a major impact for short/long term network rollout goals and budgetary plans.
PREDICTIVE CAPACITY PLANNING
This module was designed to help network engineers with the capacity study of the network and give them useful insights for the upcoming rollout plan. The aims at delivering significant information in the process of identifying problems and assign priorities on network redesign. In fact, it assists them in the detection of cells and areas with capacity issues, allows for the comparison between different frequencies and incorporates a wide range of functionalities like evaluation and forecast based on specific network KPIs, cell classification and detailed analytics on problematics cells.
DATA DRIVEN NETWORK ROLLOUT
This module assists the network engineers with a sector-based rollout plan, for instance determining the need for adding new sites or a band for relieving congestion and improve QoS/QoE. It also allows executives to have an overview of the expenditures for spectrum and network rollout. This is done through the exploitation of the available information and relevant data sources.
CAPEX and OPEX spending in RAN is a complicated task. This module offers an objective view of earnings and expenses at a site level, enriched with other information to assist CAPEX and OPEX allocation plans. Among other, it offers a prioritization of network rollout and optimization activities, calculations of earning and costs and combines information from the GeoAnalytics module to improve performance in areas of interest.