6 best practices for building an intelligent master data management strategy

6 best practices for building an intelligent master data management strategy

Data has become a powerful commodity around which the business world operates, and decision-makers are not flinching from that anymore. Now, business strategies and processes are built on the foundations of reliable data, and their consistency cannot be fractured.

However, master data inconsistencies and redundancies are not uncommon for those who have been in the business world for even a year now. The impact can be felt significantly across the different levels of the applications and systems—customers, suppliers, enterprises, and product value chains. Today, the need of the hour is beyond just formulating a data strategy. There is an urgent need for an intelligent master data management (MDM) strategy.

While master data may be working wonders at the application level, it takes no blue-sky thinker to realize that the business management needs a more uniform and consistent data availability. Master data management (MDM) maintains the single version of truth of the core data across the enterprise. This centrally governed and trusted data is used by various business units, departments, and individuals for better decision making. Apart from decision-making, MDM also plays a key role in digital transformation initiatives.

Here are 6 key aspects that you should keep in mind while formulating an intelligent MDM strategy.

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