What activity is helpful in mapping source system data for MDM efforts?

Data profiling is a crucial activity in mapping source system data for MDM efforts. Data profiling

involves analyzing data from source systems to understand its structure, content, and quality. Key

steps include:

Data Assessment: Evaluating the data to identify patterns, inconsistencies, and anomalies.

Data Quality Analysis: Measuring the quality of data in terms of accuracy, completeness, consistency,

and uniqueness.

Metadata Extraction: Extracting metadata to understand data definitions, formats, and relationships.

Data Cleansing: Identifying and correcting data quality issues to ensure that the data is suitable for

integration into the MDM system.

By performing data profiling, organizations can gain insights into the current state of their data,

identify potential issues, and develop strategies for data integration and quality improvement.

Reference:

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.

"Data Quality: The Accuracy Dimension" by Jack E. Olson.