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What are some core principles of data governance?

By Admin Account | Last updated: July 6, 2020

Data is the backbone of nearly every business, be it small, medium or large. And the rate of data generation is many times what it was in the past. Therefore, data must be managed with highest priority to achieve the desired business goals. Otherwise, the unmanaged data can ruin the business. This is why data governance is so important. Data governance can be defined as an overall management of quality, usability, availability, security and consistency of an organization's data.

There are certain core principles which drive a successful data governance implementation:

  • Recognizing data as an asset: In any organization, data is the most important asset. Data has real, tangible and measurable value, so it must be recognized as a valued enterprise asset across different layers of an organization. Data is the key influencer for organizational decision making, so enterprises need to ensure that their data assets are defined, controlled and accessed in a careful and process-driven way. As a result, management can be confident in the accuracy and the output of data.
  • Data ownership and accountability: In a successful data governance process, ownership and accountability of data have to be clearly defined. In an organization, data must be clearly defined for enterprise-level integration and it should be accessed through authorized processes only. As the data is used by all the layers of an organization, the IT department should not be the sole owner. The participation in data governance must come from all of the departments to make it a success.
  • Following standardized rules and regulations: A data governance process should follow standardized rules and regulations to avoid risks and noncompliance. Organizations should define proper rules and guidelines for things such as data access, data definition, privacy policies and security standards. These standardized policies should be adhered to strictly in order to avoid data chaos.
  • Managing data quality consistently: The quality of data has to be managed consistently from the very beginning. The enterprise data must be tested on a periodic basis against the defined quality standards.
  • Change management: It is very important for an organization to track the data changes over the time period. Therefore, the data governance process should define change management activities proactively.
  • Data audit: A data audit is a standard process in organizations. Therefore, the data governance process should support a transparent audit policy.

In short, data governance is a continuous process and it has to be managed properly over the years. The core principles should be kept simple and understandable to all the layers of an organization. Overall, participation and adherence to the key policies are the guiding factors for a successful data governance implementation.

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