Much of the conventional guidance about implementing a data governance program focuses on organizational structure and the protocols for defining and agreeing to corporate data policies. Yet, as organizations get their data governance councils set up, it is becoming clear that an effective data governance initiative must go beyond defining roles and holding council meetings. Operational data governance requires methods and tools for enforcing compliance with corporate data policies.
While data modeling, metadata management, and data quality tools have been the typical tools in the arsenal of the data steward, these technologies often focus on static data or data at rest. Organizations realize the need for visibility into how information flows across the extended information enterprise and the governance characteristics of data in motion.
Data lineage is the key to providing this visibility, and this paper examines ways that data lineage empowers data stewards to operationalize key aspects of data governance.
Data lineage augments the toolkit of an organization for empowering data stewards to implement data governance. It helps in analyzing data dependency, validating semantic consistency, and facilitates the analysis of the effects of changing data sources and requirements. Data lineage supports operational stewardship tasks, such as data quality root cause analysis and integrating data controls. It supports enforcing and reporting on data privacy regulatory compliance.
Read the 7-page whitepaper “Empowering Operational Data Governance with Data Lineage” by David Loshin to discover how we define data lineage and how data lineage supports a variety of key operational data stewardship activities. The whitepaper concludes with suggestions of some technical capabilities to look for in a solution, providing support for data lineage.