The following criteria should be considered while evaluating vendors and technologies for meeting data quality requirements in an organization:
1. Enterprise Data Quality Framework – Evaluate the degree of effort required to integrate the wide range of functional capabilities into a single architecture and product, so that end users will ideally have a single point of access and integration point for the Data Quality domain. This requirement may be a long term goal as it is almost impossible to achieve enterprise wide data quality platform from a single initiative. A multi-year program consisting of small subject-oriented projects is a more feasible approach. However, the vendor plays an important role throughout the implementation of the program, and therefore should be evaluated against this criteria. Of course, it is critical to analyze if a true enterprise wide implementation is required, as a localized departmental one may suffice; it really depends on the organization’s mandates.
2. Functionality Coverage – Evaluate the extent of functionalities an capabilities of the data quality platform/solution. The usual capabilities that are required from a robust data quality platform include data profiling, reference data standardization, value matching, data rule analysis and rules discovery, data enrichment using supplemental data feeds and data quality monitoring. Depending on the specific requirements, evaluate a platform based on the depth of coverage for these and other capabilities. Of course, a solution that offers all of these may not be a best fit for the organization’s requirements, therefore a one size fits all approach may not be ideal either.
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