Implementing Master Data Management (MDM) involves several challenges, but the disparity between data sources is often the most significant.
* Disparity Between Sources:
* Different systems and applications often store data in varied formats, structures, and standards, leading to inconsistencies and conflicts.
* Data integration from disparate sources requires extensive data cleansing, normalization, and harmonization to create a single, unified view of master data entities.
* Data Quality Issues:
* Variability in data quality across sources can further complicate the integration process.
Inconsistent or inaccurate data must be identified and corrected.
* Defining Requirements for Master Data:
* While defining requirements is crucial, it is typically a manageable step through collaboration with business and technical stakeholders.
* DBA Cooperation:
* Getting Database Administrators (DBAs) to share table structures can pose challenges, but it is not as critical as dealing with disparate data sources.
* Complex Queries and Indexes:
* While important for performance optimization, complex queries and indexing issues are more technical hurdles that can be resolved with appropriate database management practices.