What are the key principles of data governance?

Data governance ensures data is managed effectively, securely, and consistently across an organization. The key principles include accountability, data quality, and security/compliance. These principles help developers and teams build reliable systems while meeting legal and business requirements.

First, accountability defines clear ownership and responsibility for data. This means assigning roles like data stewards or owners who oversee datasets, define usage rules, and resolve issues. For example, a developer building a customer profile system might need to consult the data steward to understand how “customer lifetime value” is defined and calculated. Without accountability, teams might misuse data or misinterpret metrics, leading to inconsistent reporting or flawed logic in applications. Establishing ownership also helps streamline decision-making, such as approving access requests or updating data schemas.

Second, data quality ensures information is accurate, complete, and fit for purpose. Developers can enforce this through validation rules, automated checks, and monitoring. For instance, a null value in a required field like “user_id” should trigger an alert or block invalid data from entering a database. Tools like schema validation in JSON or constraints in SQL help maintain quality at the code level. Regularly auditing datasets for duplicates or outdated entries (e.g., removing inactive user records) also prevents errors from propagating into analytics or machine learning models.

Finally, security and compliance protect data from unauthorized access and ensure adherence to regulations. Developers implement encryption (e.g., TLS for data in transit, AES-256 for storage), role-based access controls (RBAC), and audit logs. For example, a healthcare app might restrict access to patient records to specific roles and log every access attempt to comply with HIPAA. Compliance also involves understanding regional laws like GDPR, which requires features like user consent management or data deletion workflows. By embedding these practices into system design, developers reduce legal risks and build trust with users.