From Data Silos to Knowledge Graphs: Architecting CrossEnterprise AI Solutions for Scalability and Trust
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Abstract
Data silos within and across organisations frequently hinder the implementation of scalable and trusted artificial intelligence (AI) solutions. The critical capabilities needed to overcome data last mile problems can be broadly summarised as the provision of a solid AI architecture coupled with scalable knowledge graphs. When these capabilities are realised, data silos become rest-silos—repositories that can be safely and trustworthily queried without any potential for their alteration or modification. These capabilities and their architectural imple- mentation are examined in detail. The synergistic integration of solid AI architectural principles and scalable knowledge graphs effectively eliminates the adverse effects associated with data silos. Leveraging the mediation ability of knowledge graphs, previously inaccessible data can be integrated from multiple departments, corporate entities and across business ecosystems. New product and service opportunities, together with the associated corporate business and operating models, can then be established.
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