Master Data Management (MDM)
What is master data management (MDM)?
Master data management (MDM) is a process that creates a unified dataset of customer, products and other entities across different IT systems.
It ensures that data elements and identifiers are authentic and true enterprise wide, improving the overall quality of data in an organization
Implementing master data management enhances the reliability of data used in business intelligence and analytical applications.
Importance of master data management:
Transaction processing systems are essential for business operations, while BI and analytics play a growing role in driving marketing campaigns, customer engagement initiatives, supply chain management, and other core processes.
However, many companies lack a unified view of their customers, often due to discrepancies in customer data across various systems. For instance, variations in first and last names, addresses, phone number and other attributes may lead to inconsistencies in customer records within order entry, shipping, and customer service systems. Master data management programs address this issue by harmonizing data from multiple source systems into a standardized format, thereby facilitating a comprehensive view of business entities.
What is master data?
Sometimes known as the “Golden Record” of information, master data is the core data of an organization that corresponds to their real customers, products and other entities with no deduplicates present.
Master data doesn’t include transactional data in the various data domains. Instead, it refers to a master file of dates, names, addresses, customer IDs, item numbers, product specifications and other attributes that are used in transaction processing systems and analytics applications.
Consequently, effectively governed master data is often referred to as a singular point of reference, or alternatively, a single version of truth.
Benefits of MDM Management:
· Increased data consistency: both for operational and analytical uses. A uniform set of master data on customers, products and other entities can help reduce data errors, optimize business processes and near real time business analytics.
· Improved regulatory compliance: MDM helps business manage data compliance in their organizations.
· More effective data governance: MDM also aligns with data governance initiatives, establishing guidelines, policies, and protocols for data utilization across organizations.
Key roles and participants in an MDM initiative:
Because of their complexity and their broad impact on business operations, MDM programs should involve a wide range of people in an organization. Some of the key positions and participants in the MDM process:
· MDM Manager
· Master Data Specialist
· Data Stewards
· Other Data Management Professionals
· Executive Sponsors
· Business Stakeholders
Key steps in the MDM process:
Steps required for an efficient MDM initiative sometime requires much time depending on the organization hierarchy, data sources and stakeholders, but some key steps required in every MDM process includes:
1. Identify all relevant data sources for a particular domain and the business owners of each data source.
2. Work with the various business stakeholders to agree on common formats for the master data across all the systems.
3. Create a master data model that formalizes the structure of the master data records and maps them to the various source systems.
4. Also with the stakeholders, decide what type of MDM architecture to deploy based on business needs and planned applications.
5. Deploy any new systems or software tools that are needed to support the MDM process.
6. Cleanse, consolidate and standardize data to fit the master data model, using data quality management and data transformation techniques.
7. Match duplicate data records from multiple systems and merge them into single entries as part of the final master data list.
8. Modify source systems as needed so they can access and use the master data during data processing operations.
Challenges of master data management:
Master data management (MDM) offers significant benefits as organizations expand their systems and applications. However, its complexity often limits adoption, especially in large enterprises.
- Disagreements on data standards among business units pose challenges.
- The surge in big data usage introduces complexities in managing unstructured and semi-structured data from various platforms like Hadoop clusters and data lake systems.
- Integrating acquired companies into MDM programs.
- Project scoping issues means sometime MDM often exceeds the planned timeline and the process becomes out of control.
Conclusion:
In conclusion, master data management (MDM) plays a vital role in ensuring data integrity and consistency across organizations, particularly as they expand and diversify their systems and applications. Despite facing challenges such as complexity, disagreements on data standards, and scoping issues, MDM remains essential for maintaining accurate and reliable data. Moreover, with the growing use of big data systems and the incorporation of acquired companies into MDM programs, the need for robust MDM strategies becomes even more pronounced. By addressing these challenges and embracing MDM best practices, organizations can unlock the full potential of their data assets and drive business success.
