Evolution of master data management that transpired in a decade to boost company efficiencies in managing data quality and data governance

Master data management (MDM) has evolved significantly in the last decade, driven by several factors, including the growing volume and complexity of data, increased regulatory requirements, and the growing importance of data as a strategic asset for businesses. MDM has become the foundation for data culture where people have complete trust in data to execute daily tasks, collaborate with one another, and drive decision-making.

The rapid rise in the need for digital transformation continues to drive many organisations to achieve a single version of the truth via the deployment and practices of MDM.

Moreover, automation in MDM and data quality tools have evolved since 2002 to boost company efficiencies in managing data quality and data governance.

Let us cover the 7 master data management (MDM) trends that transpired in a decade. 

Increased focus on data governance: Organisations have placed a greater emphasis on data governance to ensure the accuracy, consistency, and completeness of their master data. This includes the creation of data governance policies and procedures, as well as the establishment of roles and responsibilities for managing master data.

Greater use of cloud-based solutions: The rapid rise of digital transformation initiatives post-pandemic and consequent regulations urged organisations to have better data quality and data governance in place. The adoption of cloud-based master data management solutions has grown recently as organisations seek to take advantage of the scalability, flexibility, and cost-effectiveness offered by these solutions.

Advances in automation and machine learning: Automation and machine learning have been increasingly applied to master data management in the last decade. This includes using natural language processing, entity recognition, and semantic technology to improve the accuracy and completeness of master data which further helps organisations identify synergies between companies.

Greater use of master data management in conjunction with other technologies: Master data management has become increasingly integrated with other technologies, such as big data platforms and artificial intelligence, to gain greater insights from data.

More attention to data quality: In the last decade, organisations have been focusing more on data quality to ensure that master data is fit for its intended use. This includes implementing data quality checks and monitoring data quality on an ongoing basis. Master data management systems employ a comprehensive governance framework that ensures only cleansed, standardised, and enriched data enters your system, while supporting ongoing data validation and remediation within your system.

Greater use of master data management to support digital transformation initiatives: Master data management has become increasingly important for organisations undergoing digital transformation initiatives, as it helps to ensure that data is accurate, complete, and consistent across the organisation.

Integrating data privacy and security in MDM: With data privacy regulations such as GDPR and CCPA, privacy and security are increasingly important and integrated into Master Data Management solutions.

These combined factors have led to a greater focus on master data management as a critical component of an organisation’s overall data management strategy.

For more information on Master Data Management tools, check out MDO – An all-encompassing MDM solution that integrates seamlessly with various systems and helps in building data culture within your organisation.