Skip to main content
search

Knowledge Graphs

Fix your graph analytics and visualizations with advanced entity resolution.

Graph databases are growing in popularity due to their ability to show rich relationships and interactions between entities. They provide a powerful foundation for analyzing and exploring interconnected data using graph queries and visualizations. According to Gartner®, graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021, a trend driven by the need for faster decision-making across an organization.

Yet unresolved entity data burdens knowledge graphs with complexity, obscures true relationships and reduces the accuracy of analytics and insights. When different nodes in a graph represent the same entity or miss links (shared edges), it’s not knowledge, it’s just disconnected data. This leads to incomplete entity views, undiscovered fraud, missed business opportunities and more cumbersome compliance.

 Senzing inline imgdot left knowledge graph -Put the Knowledge in Your Knowledge
Graph with Senzing

Senzing® makes knowledge graphs easier to understand and more valuable by identifying and consolidating nodes that represent the same entity and revealing non-obvious relationships. When knowledge graphs are entity resolved, the resulting entity resolved knowledge graphs are more accurate and useful for both humans and machines. These easier-to-understand graphs deliver a significant advancement for humans trying to glean a graph’s most relevant insights.

Senzing knowledge graph knowledge graph knowledge graph -

Senzing Is a Critical Enabler for Graph Solutions

 Icon png 73 knowledge graph - Enables more accurate and insightful downstream graph analytics
 Icon png 3 knowledge graph - Makes graphs easier for humans to assimilate and understand
 Icon png 74 knowledge graph - Improves the performance and accuracy of graph-based ML models

Machine learning models trained with entity resolved knowledge graphs are more accurate and result in more reliable predictions. Without entity resolution, graph data used for machine learning models results in unnecessarily inaccurate models.

SCHEDULE A DEMO

Is Your Graph Solution Facing These Challenges?

 Senzing icon question knowledge graph - Are duplicate entities complicating or skewing your graph analytics?
 Senzing icon question knowledge graph - Is the complexity of your graphs obscuring n-degree relationships?
 Senzing icon question knowledge graph - Are your investigators wasting time looking for insight in a sea of duplicate data?
 Senzing icon question knowledge graph - Are you missing subtle relationships that are critical for understanding?
 Senzing icon question knowledge graph - Are your analytics generating too many false negatives and false positives?
 Senzing icon question knowledge graph - When you add third-party data, are you noticing more duplicates than before?

Overcome these challenges by resolving your entity data with the Senzing API.

Senzing Entity Resolution is a Critical Enabler for Knowledge Graphs

Advanced entity resolution is the crucial component – the secret sauce – that brings true utility to knowledge graphs. With deduplicated entity data, entity resolved knowledge graphs reduce erroneous outcomes and are vital for organizations looking to maximize the value of their graph solutions.

Senzing entity resolution identifies duplicate graph nodes (synonyms) even without a common key. Equally important is its capability to discern that nodes with identical keys may represent distinct entities, such as family members sharing an email address. Without high-quality entity resolution, systems erroneously merge these individuals into a single node, leading to inaccurate data representation, bad analytics and missed opportunities.

Thanks to its sophisticated relationship awareness, Senzing uncovers non-obvious relationships between entities. For example, Senzing can recognize that two entities share the same address despite the address looking very different to the naked eye.

Senzing knowledge graph entity knowledge graph -

Watch Senzing CEO Jeff Jonas Explain How Entity Resolution Improves Graph Analytics

 Icon png 74 knowledge graph - Enhancing Graph Analytics with Entity Resolved Knowledge Graphs

Senzing significantly improves graph analytics by identifying duplicate nodes and collapsing them and revealing non-obvious relationships. These capabilities are critical for executing complex queries, extracting valuable insights from graph data, and ensuring downstream machine-learning processes are being trained on more refined and accurate data.

Senzing knowledge graph enhancing graph analytics@2x knowledge graph -
Senzing knowledge graph advancing llm accuracy@2x knowledge graph -

 Icon png 74 knowledge graph - Advancing LLM Accuracy with Senzing

Retrieval Augmented Generation (RAG) dynamically enhances LLMs by incorporating timely and relevant information from external knowledge bases. The integration of RAG with entity resolved knowledge graphs ensures that retrieved information is accurate and contextually appropriate, leveraging the structured, interconnected nature of entity resolved graphs for superior contextual awareness.

Data quality and metadata are crucial for RAG, and using Senzing can significantly enhance your RAG applications.

– Ben Lorica

Senzing knowledge graph gradient knowledge graph -

Empowering Popular Graph Analytics Methods

Entity resolved knowledge graphs significantly enhance key graph analytics methods by ensuring data accuracy and connectivity:

 Icon png 80 knowledge graph - Pathing:

This method determines the most efficient routes between nodes, similar to route planning in Google Maps. It involves calculating costs such as tolls and optimizing schedules for logistics. Entity resolution ensures that all connections are accurately represented, making precise pathing possible.

Senzing knowledge graph knowledge graph -
Senzing knowledge graph nearest knowledge graph -

 Icon png 81 knowledge graph - Nearest Neighbors:

Crucial for AI-driven recommendation systems and enhancing chatbots, this method identifies similar elements within a graph to prevent inaccurate responses and hallucinations. Entity resolution removes duplicates that could skew these results, ensuring more effective AI interactions.

 Icon png 16 knowledge graph - Centrality Scores:

Identifies the most influential nodes within a network, vital for analyzing social networks or epidemiological studies like tracing “Patient Zero.” Google’s PageRank is a well-known example that relies on clear, duplicate-free data provided by entity resolution to maintain accurate scores.

Senzing knowledge graph centrality knowledge graph -
Senzing knowledge graph node link knowledge graph -

 Advanced entity resolution relationship link analysis Node/Link Prediction:

This predicts missing elements in a graph, which is essential for e-commerce recommendations or investigative leads. Clean, resolved data is crucial for training machine learning models, particularly graph neural networks (GNN), to ensure their effectiveness and accuracy.

Entity resolution corrects and prevents data duplications in graphs, which is essential for these analytics methods to function optimally, enhancing overall graph performance and reliability.

For more details, read What Are Entity Resolved Knowledge Graphs?

Senzing Entity Resolution Powers
More Effective Graph Solutions

 Entity resolution data accuracyFinancial Crime and Compliance

Trace connections between people and organizations to uncover fraud, financial crime and non-compliance.

Learn More

 Icon png 28 knowledge graph -Intelligence & Investigative Work

Enhance data-driven investigations by revealing hidden networks and relationships.

 Icon png 52 knowledge graph -Know Your Customer (KYC)

Elevate your ability to accurately on-board and continuously assess the risk of your customers or buyers and their relationships.

Learn More

 Icon png 56 knowledge graph -Customer 360

Gain complete 360-degree views of entities and their relationships to enhance understanding and engagement across all touchpoints.

Learn More

 Advanced entity resolution relationship link analysisSupply Chain Risk

Optimize supply chain efficiency and transparency by mapping and analyzing the relationships and dependencies between suppliers, partners and customers.

CASE STUDY

Aptitude Delivers Graph Solutions for Financial Crime Detection

Aptitude Global, a technology and data consulting solutions provider, recognized they needed better data matching and relationship detection for their Data Intelligence Platform. In response, Aptitude added entity resolution to their platform solutions to enhance their offering in combating FinCrime and fraud. The Aptitude solution with Senzing Inside™ creates entity-resolved knowledge graphs to fight financial crime, identify politically exposed persons and sanctioned entities and dynamically calculate customer risk.

Explore Aptitude Solutions with Senzing Inside™

READ MORE

Senzing entity resolution is a perfect fit for Aptitude. It was the best and only option that met all our requirements.

 

– Alan Brown, CTO

Senzing knowledge graph aptitude knowledge graph -

How to Get Started

To see the capabilities of Senzing entity resolution with your own eyes, you can use our Desktop Evaluation Tool and see results with your data (or our sample data) in 15 minutes or less. Or schedule a demo with one of our experts. Developers can download and evaluate the software for free with QuickStarts available for Linux or Docker.

If your team is thinking about adding entity resolution capabilities to your solution, or upgrading what you already have, don’t wait to find out what Senzing technology can deliver. Just choose one of our three getting started options and take Senzing for a quick test ride. Get started with Senzing today.

You can license the Senzing API directly from Senzing and plug it into your data fabric. Deploy and implement it yourself. If you need support, our expert entity resolution customer support is always free. If you prefer a full solution, you can also work with our partners who integrate Senzing into their specialized solutions that deliver complete 360-degree views of customers and other entities.

Senzing 15 minute laptop@2x knowledge graph -

Maximize the Value of Your Graph Solutions with Senzing

Icon png 67 knowledge graph -

Time-to-Value

Gain value quickly with fast installation, setup and deployment, minimal data preparation, and rapid data onboarding with no tuning or training.

Icon 81 knowledge graph -

Highly Accurate

Get the most accurate results from entity centric matching, relationship awareness, principle based resolution and real time learning.

Icon 82 knowledge graph -

Low Total Costs

Save on initial deployment costs and ongoing operational costs. Rapidly add new data sources and never have to reload.

CASE STUDY

Esri Delivers Geospatial Entity Resolved Knowledge Graphs

Esri – the global market leader in geographic information system (GIS) software, location intelligence and mapping – partnered with Senzing to make advanced entity resolution available to users of its enterprise knowledge graph software, ArcGIS Knowledge.

The Esri with Senzing Inside™ solution resolves entity data and identifies relationships (provided by Senzing entity resolution) with Esri spatial data, visualizing it in a single Esri ArcGIS Knowledge graph. The solution enables users to gain greater clarity and context from geospatial data. Instead of seeking entity data from multiple data sets across many feature layers, they can now see it in a single entity resolved knowledge graph.

Explore the Esri with Senzing Inside™ Partner Solution:
Senzing Advanced Entity Resolution with ArcGIS Knowledge

We welcome Senzing to the Esri ArcGIS ecosystem. When ArcGIS Knowledge users resolve entity data before adding it to their knowledge graph, they can make better decisions with greater confidence.

 

– Tim Murphy,
Director of Contextual Intelligence

Senzing knowledge graph knowledge graph -

Explore More Senzing Use Cases

 Customer 360 Customer 360

Read More

 Fraud detection Perpetual Vetting

Read More

 Icon png 110 knowledge graph - Know Your Customer

Read More
Close Menu