How Modern Data Science Teams Improve Predictive Analytics: A Manager’s Guide to Graph Data Science

To manage a successful data science team, it is important to produce the best and most reliable predictions for decision makers. A modern data science approach, using graphs, offers a unique way to analyze data to create fast, actionable insights.

Adopting a graph data science engine helps you operationalize analytics and machine learning to get to the strongest predictive models, among other advantages that we will explore.

Read this guide to discover:

How graph data science uniquely finds and connects data relationship patterns, leveraging relationships in analytics and machine learning for better predictive data.
Benefits that scale across departments and industries to show how graphs significantly improve anomaly and fraud detection, supply chain optimization, recommendation engines, and more.
The unique power of “pretuned” ready-to-use graph algorithms that can identify specific nodes of a graph and analyze relationships across the connected data you are targeting.

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