Link Analysis - Summary

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SigbayLinkAnalysisis an Interactive Data Visualization Framework allowing non-technical business users to gain actionable insights from large amounts of complex data. Purpose of Link Analysis (and any visualization) is to reduce disconnect between needs of business users and complexity of the underlying datasets.


  • Fully Interactive, every node and data element supports multiple contexts
  • Concise and Clear Presentation of Most Interesting Data Elements
  • Discovery of Any-to-Any: Relationships, Connections and Correlations
  • Automatic calculation of multiple summary, aggregate and statistical functions simultaneously over ALL data elements
  • Automatic and manual sorting by any chosen metric, order and number of connections to any other entity or group.
  • Discovery of anomalous relationships, unusual velocities and suspicious data patterns.
  • Peer groupanalysisand outlier discovery.
  • Multi-selecting, global searching and hot-keys controls over all functions.
  • Real-time REST API calls to get specific answers and retrieve/update data points.
  • Supports (requires) Splunk Accelerated Data Model to tap into large datasets dynamically

Business benefits:
  • Reduced Time to Value: single visualization renders answers on multiple and complex business questions.
  • Reduced Expertise Requirements: allows non-technical and less-technical business users to access, interact, understand and gain actionable insights from complex and large datasets
  • Reduced Costs: reduce consulting costs and requirements to build multiple dashboards, views and panels to help users understand and interact with data.
  • Increased Quality of Decisions, Reduced Business Risk
  • Human-friendly, intuitive interaction capabilities.
  • Strong support for finding hay in haystack needs. Concise presentation and sorting of large amount of information allowing to focus on essential and most interesting data elements.
  • Multiple Verticals: single interactive visualization technology supports diversified data sets, data formats, use cases and industry verticals

Implementation and Underlying Technology:

  • The UI part is driven by React (open source library developed by Facebook). React utilizing Virtual DOM approach for faster incremental HTML updates only when they are needed.
  • The data and state management part is done using MobX library.
  • The visualization part is based on D3 and SVG.
  • The overall project is bundled into a single Splunk visualization using Webpack, allowing to be used as component in the Splunk Web UI or independently by using the REST API to communicate with Splunk and other data analytical solutions

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