A Data gap Analysis follows once an enterprise has successfully designed and deployed the Data Model. The Gap Analysis includes comparative study of the data attributes as against the proposed Data Model requirements. The process has proven of great value for our clients, in managing the data quality for their enterprise data.
Starting from data extraction up to the constitution of data sets, our Data Quality exercise involves a number of adjustments, transforming data to ensure that data sets are delivered in a ready state to be further used for reporting, mining, modelling and advanced analytics. The Data Quality involves the following steps:
Our Data Quality solution is characterized by numerous data tests such as availability, completeness, compliance, accuracy and consistency tests across all data sets.
We recognize differentiating requirements across our clientele with distinct end use of data within each organization: for regulatory reporting, analytics or modeling. Acknowledging the efforts in time, material and resources expended in achieving a certain data quality level, we offer unique solutions to assist clients achieve the requisite data quality levels, based on their distinct requirements.