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The first step in the data cleansing process is understanding where data quality issues exist. We explore some common quality issues, using real datasets.
In this white paper, we look at how our graph visualization toolkits are used to extract insight from complex connected cyber data, and explore the advantages of this approach.
We look at three high-level questions you should consider when choosing a graph visualization partner, to make sure they’re up to scratch.
Artificial intelligence is changing the way organizations think about data analysis. Learn how data visualization and AI can do a lot of the heavy lifting for analysts and investigators working with connected data.
Let’s explore your data visualization options and the wider implications of your decision for the product and your stakeholders as a product manager.
Six of our successful customers explain how our data visualization SDKs made their complex data investigation and analysis tools more effective.
Take a tour of the automatic graph layouts and force-directed layouts that our customers use to make sense of their complex connected data.
An objective overview of Cambridge Intelligence and KronoGraph, the JavaScript toolkit for timeline visualization.
This report gives an objective evaluation of KeyLines and ReGraph by Bloor – an independent research and analyst house.
Find out which link analysis techniques would work the best for your industry? We look at 6 popular ways to improve investigative workflows.
This post gives practical tips to developers using ReGraph, our graph visualization SDK for React, on how to avoid common coding issues.
Want to add rich, interactive timelines to your investigative apps? Check out the top 5 use cases for timeline analysis using KronoGraph.
A starburst is when one heavily connected node dominates your graph visualization. We talk through practical techniques for keeping them out of your charts.
Discover how to eliminate the ‘snowstorm’ effect in data visualizations with data enrichment, aggregation, and entity resolution for clearer insights.
How to avoid ‘the hairball’ – showing connections that are so dense, they can’t be usefully visualized. It’s a problem that affects many large datasets.
A step-by-step guide to big graph data visualization, showing how to bring millions of connected nodes and links down to a human-friendly scale.