It is a challenging task to deal with the huge volume of security data that is generated and to harness it to draw insights or conduct forensic investigations. Many companies create a "Security Data Lake" which is a central repository that houses all the security log data from a multitude of sources, and leverage it to improve their overall security.
Collect and compile large volumes of data flowing in from a multitude of sources, applications, and endpoints, to build visual and contextual timelines for investigating threats.
Correlate disparate data sets to automatically analyze data and eliminate manual efforts to remove noise and false positives.
Utilize large volumes of stored data to develop models and proactively hunt for threats with associated context and visualization. Perform investigations at scale as data scales.
Store unlimited amounts of data ingested from any source, process data to build meaningful reports, and visualize using analytics tools.
Leverage automated data processing and enhance AI/ML models as the data volume increases with time or the number of data sources grows.
Scale easily as the attack surface grows, build intelligence reports rapidly and at scale at very low costs.
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