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A major challenge in enterprises is to bridge data silos and combine data of different formats from multiple sources. The goal is to consolidate distributed data or integrate centralized data across an enterprise and provide a holistic view on information for better decision-making. A semantic layer strategy can achieve this. Using standardized and reusable common schemas describing business objects, we can map all kinds of data into a unified information layer, which can then be queried and analyzed.
A semantic layer helps with easier, faster and high quality data consolidation and integration and thereby saves time and reduces costs. For generative AI services, it acts as a solid basis of truth – a grounding, which improves the quality of results and avoids misinformation.
Graphwise brings the semantic layer to your enterprise to harmonize data for your business processes and make generative AI easy and reliable to use.
This white paper touches on the following:
- The challenge of data integration
- Semantic data models for standardizing domain knowledge
- Enterprise-ready technology
- Building on reliable standards