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Stream analysis engine BlueBolt

Big data Suite‘s BlueBolt is a real-time streaming data analysis engine that converges and analyzes various informal human data sources and real-time machine data, such as equipment, production line logs, and sensor data. BlueBolt enables users to create optimized systems, predict production line problems, and detect abnormalities in security through real-time in-memory analysis of stream big data and complex event processing (CEP). Its strong dispersion in-memory analysis function offers the best performance to realize Operational Intelligence (OI). This includes large-scale service system operation and management, FDS (Fraud Detection System), compliance, and e-Discovery.

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< Stream analysis engine concept map >

Main Features

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Main features and specifications

It collects and refines various streaming data types in real-time (structured and unstructured), performs queries, and analyses under complex conditions. It can monitor and share in real-time by configuring a dashboard of the analyzed results and performing an alarm function when matching patterns occur under certain conditions.

  • Powerful visualization and dashboard feature

Built-in visualizations, including bar/pie/line charts and timelines, etc., provide intuition to real-time analysis results and rearrange them into an integrated dashboard to achieve analytical insights

  • Q&A-type big data integration analysis feature

Aggregate, distribute, and index the structured and non-structured data in real-time, such as system logs and sensor data, and SNS. Along with built-in functions, it can perform real-time big data analysis through search queries in various conditions.

  • Real-time in-memory analysis feature

Real-time memory loading and high-speed complex stream data analysis allow users to identify and predict hidden patterns to make data-based decisions. Furthermore, features for real-time time-series data addition, pattern analysis, and built-in function calculation are also available.

  • Hadoop, HBase, NoSQL data connection feature

Compatible with various data storage systems within the Hadoop ecosystem, such as HDFS and HBase. It enables easy real-time big data analysis by connecting to NoSQL databases like MongoDB.

  • Operation manager home screen setup

Users can check data collection status in real-time. The operation manager can also view the list of dashboards.

  • R language connection feature

Support the connection with R to perform statistical analysis, such as correlation analysis, multivariate analysis, and regression analysis.

  • Complex event processing (CEP) of stream data feature

When pre-registered patterns are detected in high-speed collected and indexed stream data, it can automatically notify the manager and respond. It enables real-time monitoring and early response analysis on specific events such as security, fraud detection, and signs of equipment abnormalities.

Main engine screen

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