BloatBelly is a Big Data Infrastructure developed by IANIC, for big data ingestion, processing, storing and disposing. It can manage and accrue numerous raw data in real-time, distinguish evident or underlying correlations, measure real-time KPIs and compare them against milestones that constitute business goals, send alerts, prompt actions and create forecasts.
The infrastructure enables the equal distribution of the huge data load from sensors and meters to different IANIC servers, under a single framework of technologies and tools.
BloatBelly makes use of a broad set of data extraction and machine learning libraries enabling the extraction of insights from the data collected. It supports simple metrics calculation, KPIs quantification, advanced statistical analysis, predictive modeling and real time analysis. All information is available via APIs to 3rd party applications for further processing and visualization.
Mechanisms for identifying incorrect or missing data and ways to handle them, data homogenization, mechanisms for data storage in different time intervals, and mechanisms for storing and analyzing historical data.
Rules engine mechanism, through which emergencies can be set that arise either directly from devices/applications or from real-time data combinations from one or multiple devices/applications. Ability to categorize emergencies and set alarms resulting from analysis of historical data. Mechanism of informing end users of the platform and/or external partners.
Sophisticated mechanisms for sorting, mining, regression and clustering on both flow data and historical and batch data. “If-then” analysis and mathematical algorithms mechanisms. Setting of entities and calendar values in order to export KPIs.
Communication via APIs both internally between the services of the platform and with devices and/or middleware of third party applications.
Ιnternal mechanisms that control the “health” of the building blocks of the solution and inform a group of users.
Secure communication with end devices and definition of which services/users see the devices and data. Encryption/decryption mechanisms for data exchange, as well as authentication mechanisms and procedures for their monitoring and renewal.
Seamless performance without degrading quality, when there is an increase in user requests, volume of data collected, stored and processed, and number of components/services that interact with the platform. Use of edge cloud technologies, such as container-orchestration systems.
IANIC offers a full range
of Big Data Services:
Ingestion, processing and management of massive sets of Big Data in real time with high security & at low cost.
Automatic triggering of actions & alerts according to thresholds set in KPIs.
Advanced visualization & reporting capabilities.
Professional support from experienced Data Scientists, DevOps, Data Analysts and Developers.