For the longest time, operational business applications ran with embedded functionality for managing master data. It was the right strategy if deployed under the assumption that companies eventually would consolidate and support all business processes on one platform, a single enterprise resource planning system. Very few organizations ever got close to realizing this vision due to continuous M&A activities and the lack of a compelling case to fully harmonize business processes and decommission all systems but one. Hence the idea of master data management focusing on only one system proved to be a mistaken and inflexible idea. That is why over the past five to eight years we have seen master data repositories emerging as distinct applications and related governance and methods acknowledged as a discipline, MDM.

Because MDM addresses core master data issues at the root, the focus has largely been on the data-producing side of the information supply chain. Meanwhile, to a large degree, the BI world has dealt with MDM-related issues as it always has: Issues were solved downstream as part of the extract, transform and load processing. The predicament is that many of the synergies that could be realized by leveraging the operational MDM discipline are often left untouched when it comes to BI. In other words, it is due time for BI to engage in true master data management. This article aims to uncover how and where to address different master data challenges and how to let both the BI and online transactional processing worlds embrace and utilize MDM on equal footing. It addresses key areas where the MDM discipline impacts traditional best practices for BI and data warehousing. In particular, MDM changes the type of data transformation and data quality management needed in the ETL layer of the data warehouse architecture.

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