master data management - 10 things to know with detail
- 1. Definition: Master data management (MDM) is a method of managing and organizing critical data to ensure consistency, accuracy, and reliability across an organization. It involves creating a single, consistent view of master data entities such as customers, products, employees, and suppliers.
- 2. Importance: MDM is crucial for organizations to improve data quality, streamline business processes, enhance decision-making, and comply with regulations. By having a centralized and standardized view of master data, companies can avoid data duplication, errors, and inconsistencies.
- 3. Components: MDM typically consists of processes, governance, policies, standards, and tools to manage master data effectively. It involves identifying master data domains, defining data attributes, establishing data governance rules, and implementing data quality controls.
- 4. Master data domains: Common master data domains include customer data, product data, employee data, supplier data, location data, and financial data. Each domain has specific attributes and relationships that need to be managed consistently across the organization.
- 5. Data governance: Data governance is the framework that defines the roles, responsibilities, policies, and procedures for managing master data. It ensures that data is accurate, complete, and secure, and that data-related decisions are made effectively.
- 6. Data quality: Data quality is a critical aspect of MDM that focuses on ensuring data accuracy, completeness, consistency, and timeliness. Data quality tools and processes are used to cleanse, standardize, and enrich master data to improve its reliability and usability.
- 7. Data integration: MDM involves integrating master data from various sources, systems, and formats to create a unified view of data. Data integration tools and techniques are used to consolidate and synchronize master data across the organization.
- 8. Data stewardship: Data stewardship is the practice of assigning responsibility for managing and maintaining master data to individuals or teams within the organization. Data stewards are accountable for ensuring data quality, resolving data issues, and enforcing data governance policies.
- 9. Data lifecycle: MDM involves managing the entire lifecycle of master data from creation to retirement. This includes data creation, data capture, data storage, data maintenance, data usage, and data archiving to ensure that data remains accurate, relevant, and secure throughout its lifecycle.
- 10. Benefits: The benefits of MDM include improved data quality, increased operational efficiency, enhanced decision-making, better customer service, regulatory compliance, and cost savings. By implementing MDM, organizations can unlock the full potential of their data assets and drive business success.