Data Quality Governance

Data quality is very important to every organization, bad data cost an organization time, money, and resources that could be prevented if the proper governance was put in to place. 

Data Governance Program Criteria:

• Support from Executive Management and all Business Units
• Data Stewardship Program 
• Cross Functional Team of Data Stewards
• Data Governance Committee

Quality Structured Data

It should go without saying but any successful project in today’s business world must get buy in from executive management and all stakeholders involved with the project. If management does not fully support a project because they see it is in there and the company’s best interest then they will remove/eliminate funding, resources and allocated time to work on the project. In essence they can render a project dead until it is official killed by the business. In addition, buy in from stake holders is also very important because they can cause delays increased spending in time, money and resources because they do not support a project.

Data Stewardship programs are administered by a data steward manager who primary focus is to support, train and manage a cross functional data stewards team.

A cross functional team of data stewards are pulled from various departments act to ensure that all systems work to ensure that an organization’s goals are achieved. Typically, data stewards are subject matter experts that act as mediators between their respective departments and IT.

Data Quality Procedures

Data Governance Committees are composed of data stewards, Upper management, IT Leadership and various subject matter experts depending on a company. The primary goal of this committee is to define strategic goals, coordinate activities, set data standards and offer data guidelines for the business.

Data Quality Policies

In 1997, Claudia Imhoff defined a Data Stewardship’s responsibility as to approve business naming standards, develop consistent data definitions, determine data aliases, develop standard calculations and derivations, document the business rules of the corporation, monitor the quality of the data in the data warehouse, define security requirements, and so forth.

She further explains data stewards responsible for creating and enforcing polices on the following but not limited to issues.

• Resolving Data Integration Issues
• Determining Data Security
• Documenting Data Definitions, Calculations, Summarizations, etc.
• Maintaining/Updating Business Rules
• Analyzing and Improving Data Quality