Gain valuable and actionable insights
ClearSkies™ Big Data Advanced Analytics Platform
AN AWARD-WINNING SERVICE DELIVERY VEHICLE
Manage & Process your Big Data Efficiently & Intelligently
The award-winning ClearSkies™ Big Data Advanced Analytics Platform stores, processes and intelligently analyzes vast volumes of both historical and current heterogeneous log and event data, in real time, in a fraction of the time needed by other SIEM platforms.
Through achieving high levels of speed and accuracy during the analysis of log and event data collected from IoT, servers, applications, network/security devices, or even user activities, the Platform maximizes the management efficiency and effectiveness of the threat detection and response process. The Platform is customer-focused, as it provides scalability and flexibility when safeguarding the reliability, availability and redundancy of sensitive information belonging to your organization.
Inherent characteristics shared by all Platform-based products
Intelligent Analysis (AI & ML Models)
Enhanced early detection of and response to targeted attacks, data breaches and/or user suspicious/malicious behavior, minimizing the “Detection Deficit”.
How it works : Utilizing HDFS capabilities, complex Statistical, Behavioral & Predictive/Machine Learning analytical models make possible the detection of abnormal behavior and/or malicious Information-Threats that would otherwise go unnoticed/undetected when using conventional Security Information & Event Management systems.
Such flexibility enables the capacity to collect, process and analyze new types of log and event data related to Internet Of Things (IoT) and Operational Technologies (OT) environments.
How it works: Capability to store, process and analyze different types of log and event data from diverse types of devices/vendors, either structured or unstructured.
Ability to process considerably more current and historical log and event data in real time in a fraction of the time.
How it works: The effectiveness of Hadoop Distributed File System (HDFS) and the MapReduce functionality allows parallel real-time processing by spanning log and event data collected across different data nodes in a single cluster, enabling achieving ten-fold processing speeds when intelligently analyzing vast volumes of heterogeneous log data.
Log and event data reliability, availability and fault-tolerance.
How it works: Log and event data span across different nodes, storing three copies of each piece of data on different DataNodes in a single cluster, providing fault tolerance. By offering a failover setup for the NameNodes that control the copy and distribution process of data, the reliability and availability of data is safeguarded.
Log and event data that were previously too expensive to store and impossible to manage are available for real-time analysis.
How it works: The analysis of vast amounts (billions) of log and event data allows for the extrapolation of more accurate results for identifying abnormal behavior and malicious or “noisy/quiet” cyber-threats.
Multitenancy architecture allows for multiple tenants’ data to be kept separate for compliance and security.
How it works: Multitenancy enables optimization of detection and response times through centralization, while maintaining a secure architecture.