Kinetica’s new platform bridges the gap between complex telecom data and non-technical users with an LLM-powered interface that converts plain English to SQL. Analyze spatial and time-series data like network performance, demand, and fraud easily.
Telecom providers rely on innumerable data points to optimize network performance, predict demand, analyze usage patterns, monitor signal coverage, ensure reliability, and detect fraud, among other factors.
However, this spatial and time series data — based on geographic boundaries and events occurring over time — is complex and difficult for nontechnical users to analyze.
“Analyzing these two types of data requires specialized skills due to their complexity and interdisciplinary nature,” Phil Darringer, Kinetica VP of product management at real-time database platform Kinetica, told SDxCentral.
In hopes of bridging this gap, Kinetica announced the availability of Kinetica SQL-GPT for telecom.
The platform consists of a database engine specifically designed for time-series and spatial analysis, and a user interface connected to a large language model (LLM) converts plain English into Structured Query Language (SQL).
“This combination of these two capabilities enables telco professionals to converse with their data,” said Derringer.
