A semantic layer is an abstraction layer within a data architecture that provides a business-friendly, consistent view of data, translating complex technical schemas into intuitive, meaningful terms for end-users and applications. It acts as a universal data interpreter.
Mechanism
This layer maps raw data from various disparate sources into logical business concepts, relationships, and hierarchies. It incorporates definitions, calculations, and aggregation rules, thereby creating a unified data model independent of the underlying physical storage structures.
Methodology
Implementing a semantic layer enhances data governance, accessibility, and consistency across an organization. It simplifies data analysis, enables self-service analytics, and ensures that all users operate with a common, unambiguous understanding of data, which is critical for informed decision-making in complex financial systems.
ETL physically moves and transforms data into a persistent repository, while data virtualization provides real-time, integrated access to live source systems.
A data fabric cuts costs by creating a virtual, intelligent layer that unifies data access and automates integration, reducing redundant infrastructure and manual effort.
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