Use Cases: Knowledge Graphs
Empower Your Data to Do More
Knowledge graphs codify data for inferring new knowledge using connections to support exploration, discovery and decisions – by human, software or AI systems.
The World Has Changed.
Knowing Is Half the Battle.
It's no secret that global stresses are straining rigid, inefficient systems to breaking points. The need for rapid reconfiguration of operations and processes is real.
To not only survive but thrive, businesses like yours need to be resilient, nimble and take creative approaches to meet these modern day challenges – using the data you already have on hand.
The good news? The new wave of data-driven advanced analytics and optimization – built on systems created to acquire and integrate adjacent information – is here to help. But taking strides toward digital transformation means you first need to turn data into useful knowledge.
Enter the knowledge graph.
Everything a Knowledge Graph Should Be
Connected & Unifying
Siloed data must be easily traversed to detect and make connections with relevant, related attributes.
Flexible & Dynamic
Easily update schemas and add new data and dynamic auto updates with intelligent labels.
Explainable & Practical
Domain knowledge that's easy to visualize and understand, with the ability to apply it to new situations.
Analytical & Scientific
Deep knowledge is derived from advanced queries, graph algorithms and data science capabilities.
Performant at Scale
Run graph algorithms at enterprise scale and get fast results for even highly complex queries.
Grow the Impact of
Your Knowledge Graph
Knowledge graphs ensure search results are contextually relevant to your needs, but that’s just the beginning.
As more and different types of data are added – and as you write-back analytics results – you're continually enhancing your knowledge graph, increasing its usefulness and value.
Using graph visualization tools like Neo4j Bloom and integrating with BI platforms then empowers you to intuitively explore graphs while sharing graph-based insights to an entirely new audience.
See how Neo4j customers have evolved their knowledge graph for even more positive business impact.
Independent Survey on Technology
Executive Priorities for Knowledge Graphs
What are technology executives using their knowledge graphs for? Read survey results from 100 executives to understand their priorities, the potential barriers to adoption, and the business outcomes they foresee.
A knowledge graph is most often used to aggregate and search large volumes of static internal data. Discover how NASA took an astronomical amount of data scattered across the organization to form a knowledge graph – with billions of nodes – so researchers can easily search their "lessons learned" database that stores crucial details from past missions.Read the White Paper
New Discoveries and Insights
Successful clinical trials depend on finding the right therapeutic experts, physicians and participants. That research takes a long time. At PRA Health Sciences, Neo4j Bloom empowers the business development team to visually explore connections and rapidly identify trusted partners.Watch the Webinar
More Accurate Predictions and Forecasting
Pulling in data from multiple sources, the U.S. Army, together with Calibre, is able to forecast the need for replacement parts, perform multidimensional cost comparison and trend analysis, inform the Army’s budget requirements process, and answer vital “what if” questions that weren't possible with their legacy systems.
Decisioning Based on Contextual Relevance
Boston Scientific prides themselves on maintaining excellence in manufacturing. By pulling manufacturing data into a Neo4j knowledge graph, they detangle complex processes by analyzing all relationships between their supply chain components and testing failures, pinpointing areas of improvement while increasing accessibility across the business.Check Out the Infographic
Active, Increased Business Agility
Owned by the world’s major airlines, ATPCO blends pricing/retailing data and systems with innovative technology to help airlines best manage their complex products in the marketplace. A Neo4j knowledge graph now powers their graph-based pricing platform. They have gone on to use Neo4j as the core of at least five of their main services, and the pricing engine has helped one startup offer an innovative, new product to the airline sector.Read the Article
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
Neo4j Amplifies Your Outcomes
Uncomplicated Streamline the process of capturing and applying complete knowledge with technology built to acquire and integrate adjacent information.
Performance Run Neo4j algorithms over 10's of billions of nodes and slash query speeds from minutes (or hours) to milliseconds.
Agility A flexible schema makes it simple to transform, reshape and export graphs, based on evolving business needs – without disruption.
Productivity Cypher is easy to learn and requires 10x less code than SQL – a win for efficiency. We also offer a wealth of resources, support and community.
Hardware Efficiency Native graph query processing and storage demands 10x less hardware than RDBMS or NoSQL graphs, enabling direct cost savings.
Trusted Leadership Neo4j is the creator of the property graph model with thousands of customers, a vibrant global community and expert service teams.
Not sure how to get started?
Our graph experts provide professional services – from onsite training to a Knowledge Graph Quick Start service – that takes you from zero to operational in as little as 8-10 weeks.
In addition, you can use our pre-built and customizable Solution Frameworks with proven code, models and components for multiple types of knowledge graphs. These supported frameworks include data models and ontologies for areas such as financial systems, supply chain, privacy compliance as well as customer, employee and patient information.