Glossary

What is Data Quality Management?

What does Data Quality Management mean?

Data Quality Management (DQM) is the discipline of establishing processes, policies, and technologies to ensure that data remains accurate, complete, consistent, and fit for purpose throughout its lifecycle.

In MRO and ERP systems, DQM focuses on maintaining high-quality spare parts, vendor, and material master data. Poor data quality can result in duplicate items, incorrect inventory levels, procurement inefficiencies, and costly maintenance delays.

Effective DQM is not a one-off project but an ongoing practice that combines people, processes, and tools to safeguard the reliability of business-critical data.

Key components of Data Quality Management

  1. Data profiling – Assessing datasets to understand current quality issues.
  2. Data cleansing Detecting and correcting duplicates, errors, and inconsistencies.
  3. Data standardisation – Applying uniform rules for naming, classification, and coding.
  4. Data enrichment Adding missing attributes and technical details.
  5. Monitoring and governance – Continuously measuring and enforcing data quality KPIs.

Why Data Quality Management is critical for ERP and MRO

High-quality data is the foundation for reliable ERP, CMMS, and EAM systems. Without DQM, organisations struggle with procurement errors, excess stock, incomplete supplier records, and unreliable reporting.

By applying structured DQM practices, organisations can:

  • Ensure consistent and accurate spare part catalogues.
  • Reduce downtime and maintenance inefficiencies.
  • Improve procurement performance and supplier collaboration.
  • Support ERP migration and digital transformation initiatives.

Sharecat Data Services delivers scalable Data Quality Management solutions, combining cleansing, standardisation, and enrichment to help clients maintain accurate, business-ready datasets for ERP and MRO systems.