Data governance is a process by which the data in the enterprise systems are managed by the availability, usability, integrity, and security, based on the internal data standards and policies. A good data governance model ensures consistent and accurate data, leading to better analytics and informed business decisions. Without effective governance, data inconsistencies in different systems across the organization will not get fixed. For example, customer names may be listed differently in sales, logistics, and customer service systems. That could complicate data integrity issues and affect the accuracy of business intelligence (BI), enterprise reporting, and spend analytics. Data governance is a collection of processes, roles, policies, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals. It establishes the processes and responsibilities that ensure the quality and security of the data used across a business or organization. Data governance defines who can take what action, upon what data, in what situations, using what methods. Data governance helps in the management of data across ERP / CMMS / EAM systems and ensures that data is consistent all across and is not misrepresented. There are some pitfalls in master data management and listed below are some reasons as to why it may fail: While implementing a Data Governance System the organizations must consider all of these pointers that might cause it to fail and always make sure to take up this process if one is completely sure about handling it well. Talk to our Master Data Governance specialist today to get insights to your industry best practices and how it can benefit your organization.