Knowledge graphs help organizations make the greater part of their enterprise data more easy to find, understand, and use, so that analysts, data scientists, and other data consumers can use data and analytics better and more frequently to drive their businesses. This interesting topic came to us from Medium in their article, “Knowledge graph adoption— sales pitch for getting executive support.“
Using the graph data model and semantics to expose both business meaning and the connections between data points connecting vast landscapes of previously siloed, complex data platforms is key for success. This approach uniquely enables enterprise goals related to information architecture. The knowledge graph approach, powered by graph and semantics, empowers more data-driven people in the business to build their own highly contextualized, enterprise-scale, analytics-ready datasets on a self-service, on-demand basis — shrinking the decision cycle while offering more complete answers and new insights.
Data Harmony is a fully customizable suite of software products designed to maximize precise and efficient information management and retrieval. Our suite includes tools for taxonomy and thesaurus construction, machine aided indexing, database management, information retrieval, and explainable artificial intelligence.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
