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Applying Knowledge Graphs in the Real World


Knowledge graphs are driving industry disruption and business transformation by bringing together previously disparate data, using connections for decision support, and adding context to AI applications.

DBTA recently held a webinar with Dr. Maya Natarajan, senior director, knowledge graphs, Neo4j and Dr. Jesus Barrasa, senior director, sales engineering, Neo4j who discussed why knowledge graphs are on the rise, how they work, and what the most popular use cases are for enterprises.

A knowledge graph is an interconnected dataset enriched with semantics so we can reason about the underlying data and use it confidently for complex decision-making, Natarajan and Barrasa explained.

Knowledge graphs tackle complex data problems at scale and are applicable for a wide range of use cases across the data spectrum. They also play an important role in various industries and are connected to a rich and deep ecosystem.

The platform connects data and its relationships to provide deep dynamic context, they said. A knowledge graph bridges together diverse and disparate data silos regardless of data type, such as structured, unstructured, and semi-structured.

It can map data and draw connections among them for the first layer of dynamic context, which provides immediate understanding. And Knowledge graphs apply semantics to provide deeper context to connected data. The deeper the context, the more powerful the insights, Natarajan and Barrasa noted.

From bridging data silos to building a data fabric to accelerating machine learning and AI adoption and providing a blueprint for digital twins, knowledge graphs are foundational and allow businesses to be competitive and thrive.

Knowledge Graphs allow you to make implicit relationships….explicit, they said.

Neo4j worked with NASA to find incidents that may have taken place during missions to prevent future disasters.

NASA used semantic search within Neo4j’s knowledge graph to comb through millions of documents, reports, project data, lessons learned, scientific research, medical analysis, geospatial data, IT logs, etc. stored nationwide.

This resulted in a quicker resolution of issues and saved $1 million in taxpayer funds, according to Natarajan and Barrasa.

An archived on-demand replay of this webinar is available here.


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