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Simple. Intuitive. Scalable.

Knowledge Graphs

A Neo4j knowledge graph is an insight layer of interconnected data enriched with semantics, so you can reason with the underlying data and use it confidently for complex decision-making.

From Graph to Knowledge Graph: A Short Journey to Unlimited Insights

Knowledge Graphs: Data in Context for Responsive Businesses

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

How Knowledge Graphs work

Drive Intelligence into Data

A knowledge graph gets richer as new data is added. Through a combination of data, graph, and semantics (meaning), you get a knowledge graph with deep, dynamic context.

1. Data

Bridge together diverse and disparate data silos regardless of data type, such as structured, unstructured, and semi-structured.

2. Graph

Map data and draw connections among them for the first layer of dynamic context, which provides immediate understanding.

3. Semantics

Apply semantics to provide deeper context to connected data. The deeper the context, the more powerful the insights.

Why Knowledge graphs

Deeper Context for More
Powerful Insights

Only graphs excel at managing connected data and complex queries, because relationships are at the core of the data model. Knowledge graphs add an additional layer of context to deepen the connections.

Bridge Data Silos

Connect and contextualize the variety of structures and formats of your data so you can operate more efficiently and effectively.

Complete Visibility

Gain complete visibility into data, processes, products, customers, and ecosystems for increased efficiency and enhanced security.

Increased Efficiency

Automate critical functions to automatically surface risk and indirect relationships, enforce dependencies and track compliance.

Improved Governance & Compliance

Track data throughout its entire lifecycle – from source to consumption – to build trust and maximize the value of your data governance.

Better Predictions for Better Decisions

Unearth highly predictive relationships for analytics and machine learning models to make more informed predictions and decisions.

Independent Survey on
Technology Executive Priorities for Knowledge Graphs

See some stats that show people are turning their attention toward knowledge graphs.

Every

Neo4j Graph Data Science project starts with a knowledge graph

Neo4j Customer Segmentation Analysis, 2020

88%

CXOs believe knowledge graphs will significantly improve bottom line

Pulse Survey, 2020

Two-thirds

of Neo4j customers have implemented knowledge graphs

Neo4j Customer Segmentation Analysis, 2020

Types of Knowledge Graphs

Actioning Knowledge Graph

A data management knowledge graph that aims to drive action by providing data assurance, discovery, or insight.

Decisioning Knowledge Graph

A knowledge graph used for analytics, machine learning or data science where the aim is to improve decisions.

With POLE [knowledge graph], what you see is what you get – there is little to no difference between our data models and conceptual models of the business problem.

Tuomas Piippo, CTO Turku City Data

Ninety percent of data scientists are using Amundsen [knowledge graph] to do their jobs on a weekly basis. We also found that this tool has increased productivity for our entire data science organization by around 30 percent.

Tamika Tannis, Software Engineer, Lyft

We used graph algorithms to find patients that had specific journey types and patterns, and then find others that are close or similar.

Joseph Roemer, Global Commercial IT Insight & Analytics Sr. Director, AstraZeneca

Using Neo4j, someone from our Orion project found information from the Apollo project that prevented an issue, saving well over two years of work and one million dollars of taxpayer funds

David Meza, Chief Knowledge Architect, NASA

Not sure how to get started?

Check out our Knowledge Graph Quick Start service that takes you from zero to operational in as little as 8-10 weeks.

You can use our pre-built and customizable Solution Frameworks with proven code, models, and ontologies.

Get Started Now
RESOURCES

Featured Content

Blog

Building the Enterprise Knowledge Graph

White Paper

From Graph to Knowledge Graph: A Short Journey to Unlimited Insights

News

Knowledge Graph Evolution: Platforms that Speak Your Language

Podcast

Facilitating COVID-19 Research with Graph Analytics and Knowledge Graphs

Article

Knowledge Graphs for Contextual AI

Case Study

UBS: Data Lineage Tool Improves Risk Management, Drives Compliance

Case Study

Boston Scientific: Graph Data Science Streamlines Complex Medical Supply Chain Analysis

Case Study

Neo4j Keeps the Army Running by Tracking Equipment Maintenance