Data Quality Process with Six Sigma

Six Sigma is referred to controlling a process to limit output defects to the minimum. A defect always should be outside customers' requirement specifications. Most companies use Six Sigma in their applications. In the industrial segments, Six Sigma is known as the goal of achieving near-perfect quality for a product or service through new or improved processes and tools.

Six Sigma and data quality improvement share the same goal of reducing defects. Data certification improvement programs are natural choices for the application of Six Sigma methodologies. Success of Six Sigma and data certification depends on the ability to measure data quality throughout the entire process. The ability to certify data is determined by the following standards:

· Accuracy
· Completeness
· Reliability
· Availability
· Timeliness
· Consistency
· Uniqueness

Controlling data quality is all about wrapping a process around the tasks of sourcing, transforming and publishing data that enable data quality or data certification. Six Sigma provides a complete framework around the collection and control of these processes to improve the level of data quality.