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To start with, let’s take a look at what data governance entails.

There are numerous definitions of data governance. Here are a few:

So to summarize, data governance is the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival and deletion of data and information. It includes the processes, roles, standards and metrics that ensure the effective and efficient use of data and information in enabling an organization to achieve its goals.

Understanding what data governance is not can help focus on what it is. The list below illustrates the types of projects where data governance is essential to be ultimately successful. However, these types of technology projects often ignore serious considerations for the principles and processes of data governance.

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In particular, data governance is not:


Change management



Data cleansing or extract, transform and load data (ETL)



Master Data Management (MDM)



Data warehousing



Database design



Database management and administration

Data governance is not meant to solve all business or IT problems in an organization. The main goals and objectives of data governance include the following.


To define, approve, and communicate data strategies, policies, standards, architecture, procedures, and metrics.



To track and