Data Quality

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Most often means consistency of data across the enterprise. Achieving data consistency is a critical objective for most DW/BI programs because it lets us build a single view of the business. In simple terms it ensures that you can correctly add up numbers from different parts of a business.

Data quality is generally understood to be difficult to measure but it is possible if you build measures for:

• Accuracy: The degree of confidence that can be placed on data being free of error or defect
• Completeness: the extent to which data is not missing and is of sufficient breadth and depth for the task at hand
• Consistency: the degree to which common data across different sources follows the same definitions, codes and formats
• Timeliness: The degree to which data is up to date
• Security: the degree to which data confidentiality, integrity and availability has been maintained
• Fit for Purpose: the degree to which data is relevant, appropriate and meets business specifications

Data Stewards. The primary goal of a data steward (also known as a data custodian) is to create corporate knowledge about its data resources and to provide legible, consistent, accurate, documented, and timely information to the enterprise. Stewardship is also tasked with ensuring that data is used correctly and to its fullest extent, but only by those individuals authorised to leverage the data.

Refer also to Data Governance