What is Data Governance? How Will it Help?

Data governance is the management of the availability, integrity, usability, and security of the data used in a company. A good data governance program includes a set of defined procedures and a plan to execute those procedures.

The initial step in the implementation of a data governance program involves defining the owners of the company’s data assets. The company must develop policies that specify who is responsible for the different aspects of the data including its accuracy, accessibility, consistency, and integrity. Also, how data will be stored, archived, backed up and protected against incidents, thefts or attacks has to be defined. And finally, a set of controls and audit procedures must be established to ensure continuous compliance with government regulations.

When Does An Organization Need Data Governance?

An organization needs to change from an informal data management to a data governance process when one of these situations occurs:

  • The organization has grown exponentially and traditional management is not able to cope with multifunctional activities related to data.
  • The data systems of the organization have become so complicated that it is not possible to deal with multifunctional activities related to data with traditional management.
  • Data architects of the organization or other groups need the support of a multifunctional program that has the vision about the concerns and data preferences of the entire company.
  • The regulations, standards, compliance or contractual requirements need more formal data governance.

When Is Data Governance Not Recommended?

It is essential to evaluate the preparation of the company for the implementation of a data governance management process. There may be a valid reason for the current informal data management model to continue to be used. In the same way, there could be a good reason for the change to be harmful to the company. There are some warning signs that you should watch out for in case data governance in your organization is counterproductive:

  • The refusal of a group of people to get involved.
  • The refusal of the management to sponsor an effort in data governance.
  • The decision to empower a group, whether external provider, partner or an internal team, to make decisions related to the data.

Stay tuned for next week when we continue the conversation on data governance, taking a closed look at the goals of data governance.

 

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