Layered Data Fusion for Federated Enterprise Analytics
Keywords:
Multi-Tier, Enterprise Extensions, Federated Insight, Insight Engineering, Multi-Tier Architecture Federation, Layered Data Models, Data Governance, Data Harmonization, Data Layering, Enterprise Data, Federated Data Model, Enterprise Data Model.Abstract
Federated Insight Engineering Through Multi-Tier Enterprise Data Harmonization presents a framework for Enterprise Data Architecture and Engineering in accordance with the principles of Data Stewardship as developed by the International Data Space Association. The framework adopts Multi-Tier Architecture as a high level design pattern while the underlying engineering foundation is derived from the principles of Data Harmonization. Emerging from these concepts, Distributed Data Layering governs Data Management, Data Governance and Data Quality across the enterprise data landscape and connects enterprises into Dataphores, gradually culminating in Data Spaces.
Business Insights are traditionally computed in a close-world scenario with a single Corporate Data Warehouse. In a Distributed Data Layering context, however, Business Insights are engineered by Federated Insight Engineering rather than explicitly queried. In Federated Insight Engineering, technologies such as Distributed Query Planning and Execution, Distributed Hyper-Querying and Integrated Knowledge Graph Maintenance enable the seamless application of Business Analytics across the Data Layers of Lateral Data Partners, thereby discovering and engineering Business Insights.
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