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Data Catalogs and Metadata Management

Metadata Repository

C&F enhances collecting static details like descriptions and data lineage by also capturing runtime data from integration systems on load times and asset utilization in Data Warehouses or Data Lakes, providing insights into usage patterns and system optimization.
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How to leverage runtime metadata for system optimization?

Data Catalogs usually collect more static information, such as detailed descriptions of all objects in the Data ecosystem in the organization and data line.We suggest gathering runtime information by collecting data from integration systems about which objects and when they have been loaded into the database. Additionally, we recommend tracking how frequently data assets are accessed and utilized. This comprehensive approach ensures a detailed understanding of data flow and usage patterns.

Real-time data insights

Runtime metadata includes data about how and when data assets are being accessed and utilized across the enterprise. Gathering this information helps organizations understand data usage patterns and optimize the systems for better performance and resource allocation.

Operational efficiency

By collecting metadata during runtime, organizations can monitor the health of their data processes in real-time. This enables quick identification and resolution of issues such as performance bottlenecks, data transformation errors, or access irregularities.

Enhanced security and compliance

Runtime metadata can provide insights into data access patterns and audit trails, which are crucial for compliance with data governance standards and regulations like GDPR or HIPAA. This type of metadata helps in implementing robust access controls and monitoring data access to ensure only authorized users are accessing sensitive information.

Improved data quality

Metadata gathered during runtime can include quality metrics and error logs. These insights are vital for ongoing data quality management, allowing teams to detect and rectify issues promptly, thereby maintaining high data integrity.

Dynamic data lineage

Understanding the flow of data through its lifecycle is crucial for debugging, impact analysis, and change management. Runtime metadata allows organizations to track data lineage dynamically, offering a real-time view of data dependencies and transformations.

Traditional data catalogs capture static metadata, such as descriptions and lineage. At C&F, we enhance this by incorporating runtime metadata, including load times and asset utilization. This approach provides valuable insights into usage patterns and system performance, enabling better resource allocation, operational efficiency, and compliance with data governance standards.

Overview

Metadata repositories, also known as metadata management systems, are a central hub where organizations can store, organize, and manage metadata. Various types of metadata can be stored in a metadata repository, including data schemas, data lineage and data flow, data quality and governance information, and data security policies, enabling metadata integration and change. By providing a unified view of metadata, a metadata repository promotes data discovery, making it easier for people to view and navigate relevant data assets. This improves data management, streamlines data integration, supports data governance initiatives, and enables business intelligence and data analytics.

Experts in the field

Michał Werner
Senior Solutions Architect/Team Leader
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