Knowledge Graphs: A Single Source of Truth for the Enterprise

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Click to learn more about author Dr. Jans Aasman.

The notion of a “single source of truth” for the enterprise has been the proverbial moving goalpost for generations of CIOs, only to be waylaid by brittle technology and unending legacy systems. Truth-seeking visions rebuffed by technological trends have continuously confounded business units trying to achieve growth and market penetration. But technology innovation has finally led us to a point where CIOs can now deliver that truth.

Graphing the Truth 

Knowledge graphs possess the power to deliver a single source of truth by linking together any assortment of data sources required, standardizing their diversity of data elements, and eliminating silos. They support the most advanced analytics options and decentralized transactions, which is why they’re now deployed as systems of records for some of the most significant, mission-critical use cases affecting our population.

Because they scale to include almost any number of applications — and link to other knowledge graphs as well — these repositories are the ideal solution for real-time information necessary to inform business users’ performances with concrete, data-supported facts. Most importantly, users can get an exhaustive array of touchpoints pertaining to any customer, product, or interaction with an organization from the knowledge graph, making it a single source of truth.

Every Answer

Since organizations can add all types of data — regardless of variation in structure, format, or data model — to knowledge graphs, they’re primed for assembling relevant data for any use case, like a 360-degree view of customers. Thus, when contact center employees are interacting with callers in real-time, they can quickly learn all pertinent information about their experiences (including their industry, purchase history, support history, and more) by accessing information from the knowledge graph. For this use case, the multifaceted utility of these databases includes:

  • Spontaneous Questions: Knowledge graphs can answer users’ spontaneous, ad-hoc questions — with legacy systems, questions often require the laborious, time consuming, and costly process of building a new data mart.
  • 360 Customer Views: Contact center agents can view a single screen revealing everything there is about a subject, like a specific customer or product. Instead of formulating individual questions, they can ask what the graph knows about something.
  • One Source: Workers can answer any question about subjects by looking at one system instead of piecing together data from disparate systems and hoping it’s accurate.

These benefits of leveraging a single source of truth substantially improve low latent customer service interactions or others in which answers are quickly needed.  

A System of Record

As knowledge graphs mature and grow throughout the enterprise, they are transforming from a separate analytic system to the “System of Record” (SOR). SORs provide two functions. For transactions, they ensure users are accessing the latest information about changing data, such as treatments and responses for healthcare patients. For data that changes less frequently, they offer traceability for the original data source. One of New York’s most prominent healthcare systems is currently leveraging knowledge graphs for a system of record. This approach enhances their worth as a single version of the truth by delivering the following critical benefits:

  • Data Source Connections: The linked data approach of these tools allows this hospital system to connect upwards of 15 different applications, all of which are accessed for the most timely, traceable information as a system of record.
  • Transactions: Transactions for various patients, medications, diagnoses, treatments, and administrative matters (like payment) are holistically managed with this system.
  • Advanced Analytics: The provider is also able to use data from its knowledge graph to prepare and run advanced analytics on its myriad patients. That data can be codified according to specific malady, patient type, treatment type, and other categories for low latent, actionable information.

By organizing each of these capabilities — which typically involves numerous backend systems for most providers — within a single, comprehensive knowledge graph framework, this healthcare system illustrates the utilitarian value of this approach for furnishing a single version of the truth.


The technology fortifying these semantic repositories excels at providing a single version of the truth, primarily because of its expansiveness, which includes both quantities of data and use cases. Because of their standardized data models, vocabularies, and terminology systems, users can always expand these graphs to incorporate additional nodes to aggrandize their knowledge of any subject — such as the COVID-19 health crisis.

Still, their applicability to enterprise use cases is perhaps even more compelling. Properly architected solutions can accelerate time to value for cybersecurity and fraud detection use cases by amalgamating information from any number of disparate systems, so they don’t have to be individually cross-referenced.

The Truth

Knowledge is the foundation of the truth. Knowledge graphs harmonize respective data points, sources, and perspectives while co-locating them in a dependable system of record. They make a single source of truth a tangible reality, one well worth the wait of the decades of myths attached to this vision.

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