Importance of data governance & management in data-driven organizations

Data Governance

Data governance is about the how, who, why, when, where, what of DATA. It is about assigning control over data assets. It is about the use of those data assets. It is a practice of making strategies for managing, allocating, and organizing data and hence giving you clear insights to make better decisions for your company. Additionally, proper data governance reduces data management costs and lightens the IT team’s overheads. From an enterprise organization’s perspective, it’s imperative to have appropriately defined the 5Ws and 1H.

As an example; If you are in sales incentives or sales operations, data governance should focus on the following main areas:

  • Data availability & timeliness
  • Usability & consistency
  • Data transparency
  • Data quality
  • Data integrity (It means maintenance and assurance of data accuracy, consistency and completeness. It also ensures data validity and reliability)
  • Data security ( It means protecting data from digital attacks. It also protects data from unauthorized actions such as cyberattacks)

Data Policies

data driven

Data management refers to data standards, processes, guidelines, and principles. These all tell us about how to put in place data decisions. Data management is the execution and implementation part. It is the technical implementation of data governance. They help in making decisions about data. You need data standards and rules to make a proper data policy. When you prepare appropriate policies for your data, it helps you to take control of it. All the data is clear and visible. These policies will tell you how to use data and in which manner. Policies help you with the proper implementation of data details. A data policy should be maintained close to the source and should be accessible. With proper implementation, you can access your data without any hassle. It ensures that data is reliable and timely available.

Improper or lack of data governance & management leads to data delays & inaccuracies that lead to missing deadlines and eventually dissatisfied & burnt out data operations team.


Although both of them are necessary for our business, they work alongside and together. The goals of both of these are almost similar. They both create a solid data foundation and give clarity about the data. They both maintain and protect data and are like two wheels of the cycle. Without a proper implementation policy, you can't govern your data. And without data governance, you can’t put in place anything. That’s why you need to give attention to data management as well as to data governance and can’t depend on any one out of them.

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Cloud platforms, information management and advanced analytics for the life sciences industry