Comptel Corporation: Extracting Intelligence from Data

Data scientists typically have to spend most of their time on data wrangling and janitorial data work before they can get into actual analytics and intelligence extraction. These challenges are ripe in M2M environments. Managing the sheer volume of connected devices and sensors, and refining and monetizing the huge variety of data produced by the IoT aggravates the aforementioned scenario.

But a firm that has been handling business-critical data since 1986 and currently processes 20 percent of the world’s mobile usage data—which can reach 500 TB a day per telco operator customer—can alleviate these impediments.

“Comptel’s performance and scalability makes us a significant player in the marketplace,” says Mikko Jarva, CTO, Intelligent Data, Comptel, who helps digital and communications service providers manage surging data volumes through its unique DATA REFINERY solution.

“The DATA REFINERY analyzes in-stream data and drives better business decisions and automated actions from M2M data sets,” informs Jarva. The solution integrates with any technology or third-party solution, hence fusing well with M2M providers’ existing environments and adapting to any upgraded ecosystems.

“Once DATA REFINERY is deployed, we can easily introduce “plug-and-play” SOFTBLADES, for example,for Operational Intelligence, to help customers quickly adapt to changing business needs,” says Jarva.

Comptel beefs up its arsenal with DATA FASTERMIND analytics, which embeds seamlessly into DATA REFINERY, injecting intelligence and enriching decision-making capabilities in data streams. DATA FASTERMIND is supported by automated, machine-learning procedures, and includes pattern matching, anomaly detection and various predictions performed in real time.

Jarva notes, “Typically, only 20 percent of telco operators can consistently turn data insights into actions due to disconnected offline processes involving data integration, storage, analytics and actions.”

Comptel battles this hindrance with its INTELLIGENT FAST DATA principle through which integrated data is analyzed and refined into actions immediately.

"We know how to do massive data integration in an effective, efficient way, scaling up to high data volumes and designing solutions that manage hundreds of complex data streams easily," continues Jarva.