Data Quality
Data Integrity and Data Correctness
We will measure defects in terms of integrity and correctness. Data integrity refers essentially to the structure in which the data is housed – these are the data base specialist areas of identity, reference, cardinality, value, and data dependency integrity issues. Data Correctness means the degree to which the data can be used as a reliable and trustworthy source for business use, e.g. completeness, validity, accuracy, precision, consistency.
Information Quality
The degree to which the presentation makes the information useful and understandable, i.e. has the data has been translated for its intended use.
We measure defects in terms:
Defects in the raw materials, i.e. the data. These defects occur when using the wrong data, or when using data of poor quality.
Presentation defects occur when information is delivered in a form that is unreliable, inconsistent or subject to misunderstanding. Presentation quality means that information is delivered in a useful and understandable form.Comprehension – is all the information delivered which is necessary to meet the customer needs.
Delivery The degree to which the timing and location of the delivery of the BI meets the needs of the customers. We measure the defects in terms of
§ Velocity
§ Availability
§ Response time
People and Systems
The degree to which the receiver of the information translates that information into decisions and action to return value to the organization. We measure defects in terms:
§ Receiver Knowledge Base
§ Decisions, Actions and value to organization
The Six Sigma Way: Defining Quality in terms of metrics which describe Customer Needs
A Critical to Quality characteristic usually must be interpreted from a qualitative customer statement to an actionable, quantitative business specification. In other words, CTQs are what the customer expects of a product. We convert quality expectations expressed by the customer into measurable terms.