Search & Data Discovery

As data volumes continue to grow with unstructured data leading the growth, traditional techniques for business intelligence do not provide the required speed, ease and access to information. 

Search and Data Discovery tools bridge this gap with :-

  • Fast access to textual data across sources

  • Ability to filter and group data based on attributes in structured as well as unstructured data

  • Capabilities to visualize data and discover new patterns

  • Provide a framework to establish and validate hypothesis

It is important that organizations develop a strategy to leverage Search and Visualization capabilities for internal data. We provide you services to define the strategy and also implement it.

Following are use cases based on Search & Visualization. All use cases are based on Elasticsearch platform.

  • Security Analytics

  • Log Analytics

Security Analytics

Cyber attack comes unannounced. Traditional SIEM solutions provide rules to handle known attacks from known sources. However to identify unknown attacks from unknown sources, you need a system that is fast and scalable with capabilities to detect anomalies and alert about attacks before they occur. Security Analytics based on Elasticsearch provides you these capabilities. It can co-exist with your SIEM investment.  The following data can be ingested by the system to determine anomalies :

  • Authentication logs

  • Audit events

  • Netflow

  • DNS traffice

  • ArchSight SIEM data

Log Analytics

Systems across the enterprise generate logs which provide both system information as well as business metrics. Implementing a search based analytics solution utilizing these logs provides the following capabilities :

  • Real-time application level monitoring

  • Real-time business health monitoring

  • Early warning alerts for usage spikes

  • Correlate business metrics, usage statistics with system performance

  • Support planning by forecasting spikes

  • Facilitate faster RCA of issues and reduce system downtime