Data Quality Improvement

The Data Quality Improvement Service is provided through a number
of phases of activity.

The first priority is to obtain a clear and factual baseline for your current Quality levels, if improvements are to be measurable and quantifiable.

This baseline is determined, along with the identification of specific data quality problems, in the Quality Assessment Phase.

We will identify, for example, the following issues as related to your data:

• Completeness
• Relevance
• Validity
• Accuracy
• Timeliness
• Consistency
• Clarity
• Interpretation.

Once the current situation has been objectively assessed, we set about determining the best Plan of action, based on your particular problems and your business priorities. The impacts, associated with the issues identified in the first phase, are quantified and these effects are used to assist in determining the preferred approach to be taken to improve your data quality.

The next phase of the Quality Improvement Service addresses the Problem Detection and Analysis of each and every occurrence of the problems to be solved. These activities build on the earlier investigations completed during the Assessment & Planning phases. However extreme care is taken here to uncover all business requirements, to identify all compliance and audit constraints that must be applied to the correction work and to identify any exceptions that exist in respect of the problems under investigation. All of this investigation is completed prior to the actual correction activities taking place and ensures that the correction undertaken will not further corrupt the data and will meet the stipulated governance requirements.

The next phase of activity deals with the actual Correction activity. Ideally the fix is first applied to the process or system that has generated the incorrect data. Thereafter the data itself is cleansed. Care is taken in this phase to ensure the traceability and audibility of all corrective activities, so that any subsequent queries can be answered.

The final phase is the check and balance step where the improvements are checked and the quality levels re-measured. This Measure Improvements step can and should be repeated periodically to constantly assess the Quality levels in the organisation and timeously address any new problems that may have arisen.

InfoBlueprint can assist you to cleanse and enrich your data, guided by this DQI Blueprint methodology, which can be defined and implemented to suit your priorities, timescales and budget. Our quality experts will assist you to implement the actions to improve the existing data, resulting in higher reliability, lower errors and risk, and better business overall.

As a result of this engagement the quality and reliability – and thus the ‘value’ - of your data will be dramatically improved. Corrective improvements are important because they address today’s problems, produce an immediate business benefit and show the tangible value of managing Data Quality.

However, corrective improvements may not eliminate the root cause of the quality problem: new data entering the systems (and the business information derived from it), may continue to exhibit the same problems which were identified in the analysis phase. To prevent the same problems from recurring, there is a need to implement ‘preventive’ improvements, which usually involve optimization of the data gathering or transformation processes along the identified Information Value Chains.

To sustain high levels of data and information quality in your organisation, we therefore recommend that you consider the additional InfoBlueprint services provided in the Information Resource Management service.