We offer Data Quality Management. This is carried out in the following 5 phases:

• Identify & Measure Data Quality: This is a key first step, as the ability to understand the up-front level of data quality will form the foundation of the business rules and processes that will be put in place.
• Define Data Quality Rules & Targets: Once the initial data quality assessment is complete, the second part of the analysis phase involves scorecarding the results in order to put success criteria and metrics in place for the data quality management initiative.
• Design Quality Improvement Processes: This phase involves the manipulation of the data to align with the established business rules.
• Implement Quality Improvement Processes: Once the data has been standardized, the second phase of the enhancement process involves the identification of duplicate data and taking action based upon the business rules that have been identified. Since data quality is an iterative process, the rules to identify and address duplicate data will continue to evolve with an organization.
• Monitor Data Quality Versus Targets: The ability to monitor the data quality processes is critical, as it provides the organization with a quick snapshot of the health of the data within the organization.