Documentation
Explore visualization-first strategy, options, and workflows through our white papers and technical documentation.
Rapid Threat Response with Automated Feature Extraction
Learn how rapid graph visualization, exploration, and analysis supports effective risk management for enterprise-scale data in real time.
Graph Visualization for Enterprise Data Products
Visualize the iterative processes of data discovery, exploration, modeling, and analytics for the delivery of enterprise data products.
Accelerating Fraud Detection with Visualization First Analytics
Pinpoint focus to fraud detection with rapid views of the connections and pathways between individuals and the assets they control.
Provisioning Twitter Data for Exploratory Analysis
Walk through a big data workflow designed for researching social media sentiment that provides timely exploration and analysis of big data in near real time.
Cloud Services for Graph Data Provisioning
Channel serverless provisioning to help focus resources on iterative exploration of the stories that graph data can tell.
Frequently Asked Questions
Does Kineviz have documentation for enterprise graph visualization?
Yes. Kineviz's documentation page offers white papers and technical documentation covering visualization-first strategy, options, and workflows. Topics include graph visualization for enterprise data products, rapid threat response with automated feature extraction, fraud detection, cloud services for graph data provisioning, and dedicated guides for GraphXR Explorer for BigQuery and GraphXR Explorer for Spanner Graph.
What is visualization-first analytics?
Visualization-first analytics puts interactive graph visualization at the center of data discovery, exploration, modeling, and analysis. Kineviz documentation describes using this approach to accelerate fraud detection, support rapid threat response through automated feature extraction, and deliver enterprise data products by visualizing the iterative processes of discovery, exploration, modeling, and analytics.
How does graph visualization accelerate fraud detection?
Graph visualization accelerates fraud detection by giving rapid views of the connections and pathways between individuals and the assets they control. Kineviz's documentation, "Accelerating Fraud Detection with Visualization-First Analytics," explains how pinpointing focus to these relationships speeds investigation, complemented by guidance on rapid threat response and real-time risk management for enterprise-scale data.
Can I use Kineviz to visualize BigQuery data?
Yes. Kineviz offers GraphXR Explorer for BigQuery, documented on the Kineviz documentation page alongside GraphXR Explorer for Spanner Graph. These resources support visualizing and exploring cloud-hosted graph data, part of Kineviz's broader coverage of cloud services and serverless provisioning for iterative exploration of the stories graph data can tell.
How do you visualize enterprise data products with graphs?
You visualize enterprise data products by mapping the iterative stages of discovery, exploration, modeling, and analytics into an interactive graph. Kineviz's "Graph Visualization for Enterprise Data Products" white paper walks through this workflow, and related documentation covers cloud services for graph data provisioning and channeling serverless resources toward iterative exploration.
What documentation does Kineviz provide for real-time threat response?
Kineviz documents rapid threat response with automated feature extraction, showing how fast graph visualization, exploration, and analysis supports effective risk management for enterprise-scale data in real time. The documentation page also links to a Help Center and covers workflows like provisioning Twitter data for near-real-time social media sentiment analysis.