Unified Data Models refer to standardized, consistent frameworks for organizing and representing data across disparate systems and applications within an enterprise or ecosystem. Their purpose is to eliminate data silos, improve data interoperability, ensure data consistency, and facilitate accurate analytics and reporting across an organization’s technological infrastructure.
Mechanism
This mechanism involves defining a common schema, data types, and relationships that all connected systems must adhere to when storing, processing, and exchanging information. Data transformations are applied at integration points to convert system-specific data into the unified format. This ensures a coherent information flow, allowing various modules, from trading engines to risk management systems, to interpret and operate on the same semantic understanding of data.
Methodology
The methodology for implementing unified data models centers on enterprise-wide data governance, standardization, and the adoption of canonical data formats. It adheres to principles of data integrity, architectural coherence, and efficiency in information retrieval and processing. In the context of crypto investing and smart trading, this approach is crucial for consolidating market data, client information, and transaction records, enabling comprehensive risk assessment and robust request-for-quote (RFQ) and institutional options trading operations.
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