Knowledge graphs were discussed in several presentations – a metadata-related topic.
According to Gartner, “Knowledge graphs are machine-readable representations of the physical and digital worlds. They include entities (people, companies, digital assets) and their relationships, which adhere to a graph data model – a network of nodes (vertices) and links (edges/arcs).”
The EDM Council, presented by Elisa Kendall, “promotes russia whatsapp number data adopting data content standards to promote innovation across industries.” It does this by developing and standardizing industrial ontologies.
Knowledge graphs enable data integration via semantic layers.
According to Dan Collier and Jeremy Debattista, implementing knowledge graphs requires a mindset adjustment to embrace data “as a valuable asset, one that could fuel growth and success.” This includes training staff, preparing data architecture, integrating and interlinking data assets, and improving data quality.
Knowledge graphs enhance the existing business processes, allow for the representation of diverse data sources, relationships, and metadata, help map models of business domains, create a foundation for data governance, and ensure data processing transparency by documenting data lineage.