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.

Reference:

DAMA-DMBOK (Data Management Body of Knowledge) Framework

CDMP (Certified Data Management Professional) Exam Study Materials