Governance

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Data Governance

Companies know that in order to be successful, their assets, people, finances, technology, and products, must be managed. The use and value of data continues to grow exponentially, and companies have begun to recognize that data is a core corporate asset that should be managed as well.

Data management or “governance�? is naturally performed in most organizations to some degree. Typically, there are individuals or groups in both business and IT that are considered corporate data experts. They are the foundation for a governance program.

Although governance is sometimes mistakenly viewed as a method to control or limit, the true purpose of a data governance program is to empower an organization with appropriate access to shared, actionable information. The discipline of managing or governing enterprise data, assures the availability, integrity, usability and security of the data that is ultimately used for decision-making. By managing or “stewarding�? data as a key enterprise asset, organizations are empowered to make timely, informed decisions.

Effective data governance:

Builds and strengthens corporate relationships

Simplifies overly complex environments

Minimizes siloed systems and departments

Increases speed-to-market

Resolves inconsistencies and inaccuracies

Reduces redundant work effort

implemented incrementally, with smaller efforts serving as prototypes. Focus can be placed on specific data domains, applications, or business units. Governance can evolve into an integral part of the corporate culture, demonstrating value along the way.

There is no one best way to implement a data governance program. Careful consideration should be given to the corporate culture. Whether an organization is initiating a governance program or formalizing an existing one, it can be non-intrusive.

These bullets illustrate the above approach:

Work within the corporate culture/environment, adjusting and customizing where appropriate

Begin with a core set of people who already have formal or informal data or information accountability

Put structure around existing processes and procedures, while streamlining and formalizing current behaviors (implement incrementally, focusing on smaller efforts first, which serve as prototypes)