Which action best addresses inconsistent data definitions between departments?

Implementing data governance provides a structured framework for managing data across an organization, which is essential for addressing inconsistent data definitions between departments. Data governance involves creating policies, procedures, and standards that define how data is to be handled, ensuring that all departments adhere to a unified understanding of terms and definitions.

Through data governance, organizations can establish a common data dictionary and ensure that all stakeholders are on the same page regarding the meaning of various data elements. This facilitates consistency in data usage and interpretation, thereby reducing confusion and improving communication across departments. Additionally, data governance sets up accountability and oversight, allowing for the continuous refinement of definitions and practices as organizational needs evolve.

While other options like standardizing software tools, conducting regular data audits, or providing training programs can contribute to improving data practices, they do not directly address the root cause of inconsistent data definitions as effectively as a well-structured data governance initiative. Standardization of tools may still result in inconsistent definitions if the underlying governance framework is absent. Regular audits and training programs, while beneficial, focus more on compliance and technical skills rather than establishing a shared understanding of data across the organization.