Getting to Know your Data through Knowledge Graphs
Graphs exist everywhere and you are familiar with many types: line graphs, scatterplots, bar charts, etc. These graphs all have situational merit, but they are not knowledge graphs. It’s possible you’ve never heard of a knowledge graph, but you’ve undoubtedly benefited from its functionality. Knowledge graphs power Google searches, Netflix recommendations and provide the foundation for AI, like Amazon’s Alexa. Consumers are benefiting from the interconnected simplicity created by knowledge graphs, so why isn’t your business?
As a business leader, you likely know the value of your organization’s data, but I am willing to bet you don’t know the shape or visual representation of your data holistically. The shape of your data is innately important as you look to achieve true data governance and create business insight. Why? Well, because when knowledge graphs are applied to business data, it results in highly adaptable and scalable visual representation of concepts and relationships, which simplifies how insights are formed. Here are some ways in which your business could benefit from knowledge graphs:
Visual data discovery: knowledge graphs can be used as an interactive map that users can query and navigate easily. Connections between datasets provide context, and representing the data through shared vocabulary drives participation and higher engagement from all business segments. All while enabling your organization to establish how the data is accessed: rules around visibility and privacy, ownership/stewardship, data lineage tracking and integration with applications.
The use of this conceptual, relationship-based representation of data enables all teams to speak the same language, as it works as a visual, interactive glossary that you can use to query all your data without writing any code.We’re talking about bridging the gap between your data segments and your business segments, making insights available to the necessary employees safely without the siloed friction. Knowledge graphs are a powerful way to represent data that integrates the domain knowledge of each team in the organization with the data available to them.
Knowledge graphs are foundational for readying an organization for AI and Machine Learning because they inherently capture metadata. This gives context to actual data. They are perfect for advanced data usage that thrives on the relevance of data, much of which can be determined through context.
Imagine a reality where data insights are self-service and promote autonomy, without leading to inconsistencies across teams. One where data discovery is agile and ROI is high, because you are leading a data-empowered organization. A reality where AI and Machine Learning pull you far ahead of your competition because the data that empowers it is high-quality and easily accessible and digestible by algorithms. AfterData offers this augmented data reality by use of knowledge graphs. It is the core tech of our Data Governance platform, fueling our nimble and simple solution.
