Standardized Enterprise Metrics: A Framework for Consistency and Efficiency through Federated Data Management

Authors: Dinesh Thangaraju

DOI: https://doi.org/10.5281/zenodo.15054637

Short DOI: https://doi.org/g8838f

Country: USA

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Abstract: In today's data-driven business landscape, organizations face the challenge of establishing a cohesive and consistent approach to measuring key performance indicators (KPIs) across the enterprise. This paper explores a framework for implementing standardized enterprise-level metrics through the use of unified data pipelines and a federated model of data domain ownership. Many organizations struggle with siloed data and fragmented reporting, leading to inconsistent metrics and a lack of a single source of truth. The proposed framework addresses this issue by establishing a centralized metrics catalog while maintaining distributed ownership of data domains. This approach empowers individual business units to own and manage the data relevant to their operations, while ensuring that the resulting metrics adhere to enterprise-wide standards. The key principle underlying this framework is "automate once, use everywhere." By automating the data transformation and metric calculation processes, organizations can ensure consistency in reporting and analysis across the entire enterprise. This not only improves efficiency by reducing manual effort, but also enhances the reliability and trustworthiness of the data-driven insights. For example, consider the critical business driver of revenue. Through the federated data management model, the finance team may own the revenue data domain, while the sales team manages the customer and transaction data. By aligning these data sources and automating the revenue calculation, the organization can generate a standardized revenue metric that is consistently applied across all business units, providing a clear and unified view of this crucial performance indicator. By adopting this framework, organizations can establish a centralized metrics catalog that serves as a single source of truth, while empowering individual teams to maintain ownership and control over their respective data domains. This approach fosters collaboration, enhances data quality, and ensures that critical business metrics are measured consistently and efficiently across the enterprise.

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Paper Id: 232263

Published On: 2022-09-03

Published In: Volume 10, Issue 5, September-October 2022

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