What Is Data Governance?
Data governance ensures data meets regulatory requirements, compliance standards, and ethical guidelines before it moves or gets used. Without governance, organizations face violations, fines, and reputational damage.
Automate compliance, stewardship, and regulatory requirements at the source.
Data governance ensures data meets regulatory requirements, compliance standards, and ethical guidelines before it moves or gets used. Without governance, organizations face violations, fines, and reputational damage.
How Expanso implements each Gartner capability
Ensure data meets regulatory requirements like GDPR, HIPAA, CCPA.
Enforce data sovereignty and regulatory policies (like PII sanitization) before data leaves its country of origin. 'Respectful to national sovereignty.'
Control how data is used, shared, and derived downstream.
Securely 'fan out' data. Send sanitized, aggregated data to your central warehouse while shipping sensitive, raw data to a secure audit archive. You control what goes where.
Ensure AI models are trained on fair, diverse, and trustworthy data.
Ensure your data is fair, diverse, and trustworthy by filtering and balancing datasets before they are used to train models.
Data with PII crosses borders or enters wrong systems. GDPR/HIPAA violations result in fines and audits.
Enforce data sovereignty at origination. PII masked or encrypted before data leaves its source. Automated compliance.
Once data reaches warehouse, anyone can access it. No way to enforce 'need to know' or usage policies.
Define usage policies at source. Send different data subsets to different destinations based on purpose and authorization.
Training data reflects historical biases or lacks diversity. Models perpetuate unfair outcomes.
Filter and balance training data at source. Ensure diversity, fairness, and representativeness before model training.
Define governance rules (PII masking, data sovereignty, access controls) once. Enforce automatically at every source.
Send different data representations to different destinations. Raw data to secure archive, sanitized data to warehouse, aggregates to analytics.
Every governance action logged immutably. Show auditors exactly what happened to data from creation to destination.
Mask patient identifiers before data leaves medical devices. PHI never enters warehouse in raw form.
Keep EU customer data in EU infrastructure. Only aggregated, anonymized data crosses borders.
Balance demographic representation in training datasets at source. Build fairer AI models.