Description

Introduction:

This training focuses on managing, governing, and ensuring the quality of data within the DVM 360 platform. Participants will learn best practices for data stewardship, standardization, validation, and compliance, enabling accurate, reliable, and trusted data for business operations and analytics.

Prerequisites:

• Basic understanding of DVM 360 functionalities

• Familiarity with data management concepts (data lifecycle, metadata, master data)

• Awareness of data governance frameworks and standards

Table of Contents:

1. Introduction to Data Management in DVM 360
   1.1 Overview of data management principles
   1.2 Importance of data governance and quality
   1.3 DVM 360 architecture supporting data management

2. Data Governance Fundamentals
   2.1 Data ownership and stewardship
   2.2 Policies, standards, and procedures
   2.3 Roles and responsibilities in data governance

3. Data Quality Management
   3.1 Data profiling and assessment
   3.2 Validation rules and error detection
   3.3 Data cleansing and enrichment techniques
   3.4 Monitoring and reporting data quality metrics

4. Master Data Management (MDM) in DVM 360
   4.1 Identifying critical data entities
   4.2 Master data creation, consolidation, and maintenance
   4.3 Handling duplicates and conflicts

5. Data Lifecycle and Metadata Management
   5.1 Data creation, usage, archiving, and deletion
   5.2 Metadata management and documentation
   5.3 Ensuring data traceability and lineage

6. Compliance and Regulatory Considerations
   6.1 Data governance and compliance frameworks (GDPR, HIPAA, ISO 8000)
   6.2 Audit trails and reporting
   6.3 Risk assessment and mitigation

7. Advanced Practices
   7.1 Automating data quality checks
   7.2 Data governance dashboards and monitoring
   7.3 Integration with external data sources

8. Practical Labs and Case Studies
   8.1 Implementing data governance policies in DVM 360
   8.2 Performing data profiling and cleansing
   8.3 Monitoring data quality KPIs

By the end of this training, participants will be able to implement robust data management and governance practices in DVM 360, ensuring data quality, compliance, and reliability. Proper data governance supports better decision-making and operational efficiency.