Enterprise Data Management Checklist

A comprehensive checklist for implementing and maintaining enterprise-grade data management practices, focusing on data governance, quality, master data management, integration, privacy, and analytics. This checklist covers essential data management principles while embracing modern data architectures and practices.

Data Governance

Required

Governance Framework
Establish comprehensive data governance framework and policies.
Data Ownership
Define data ownership and stewardship roles and responsibilities.
Data Standards
Establish data standards and metadata management practices.
Policy Enforcement
Implement data governance policy enforcement and monitoring.

Suggested

Governance Tools
Implement data governance and catalog tools.
Data Council
Establish data governance council and regular reviews.

Data Quality

Required

Quality Framework
Establish data quality framework and metrics.
Data Validation
Implement data validation rules and checks.
Quality Monitoring
Implement data quality monitoring and reporting.
Data Cleansing
Establish data cleansing and enrichment processes.

Suggested

Quality Automation
Implement automated data quality improvement processes.
Quality Scoring
Implement data quality scoring and assessment framework.

Master Data Management

Required

MDM Strategy
Define master data management strategy and architecture.
Data Models
Establish master data models and hierarchies.
Data Matching
Implement entity matching and resolution processes.
Change Management
Establish master data change management processes.

Suggested

MDM Tools
Implement master data management tools and platforms.
Data Hierarchy
Implement hierarchical data management and versioning.

Data Integration

Required

Integration Strategy
Define data integration strategy and architecture.
ETL Processes
Implement ETL/ELT processes and monitoring.
Data Pipeline
Establish data pipeline architecture and monitoring.
Error Handling
Implement error handling and recovery procedures.

Suggested

Real-time Integration
Implement real-time data integration capabilities.
API Management
Implement API-based data integration management.

Data Privacy & Security

Required

Privacy Framework
Establish data privacy framework and policies.
Data Protection
Implement data protection and encryption measures.
Access Controls
Implement data access controls and monitoring.
Compliance
Ensure compliance with privacy regulations (GDPR, CCPA, etc.).

Suggested

Privacy by Design
Implement privacy by design principles in data architecture.
Data Masking
Implement data masking and anonymization capabilities.

Data Analytics

Required

Analytics Strategy
Define data analytics strategy and capabilities.
Data Warehouse
Implement data warehouse/lake architecture.
BI Platform
Implement business intelligence and reporting platform.
Data Models
Establish analytical data models and metrics.

Suggested

Advanced Analytics
Implement advanced analytics and ML capabilities.
Self-Service Analytics
Implement self-service analytics capabilities.

Data Operations

Required

DataOps Framework
Establish DataOps practices and automation.
Monitoring
Implement data operations monitoring and alerting.
SLA Management
Establish data SLAs and performance metrics.
Incident Management
Implement data incident management procedures.

Suggested

Automation
Implement automated data operations and orchestration.
Cost Management
Implement data cost monitoring and optimization.