Data Management Architecture defines the comprehensive structure and operational framework for how data is acquired, stored, processed, and utilized across an organization’s systems. This is particularly critical in data-intensive environments like crypto trading, establishing principles for effective data governance and accessibility.
Mechanism
This architecture includes various layers: data sources (e.g., exchange APIs, blockchain nodes), data ingestion pipelines, storage solutions (databases, data lakes), processing engines (batch, real-time), and data consumption interfaces (analytics tools, trading algorithms). Data flows are engineered to ensure consistency, accuracy, and timely delivery for diverse operational and analytical needs.
Methodology
The strategic approach prioritizes data integrity, security, and scalability, aligning with regulatory requirements for data provenance and auditability. Key principles involve designing for high availability, implementing robust access controls, and establishing clear data ownership and lifecycle policies to support complex trading strategies and risk reporting within the dynamic crypto landscape.
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