Data with poor quality is inappropriate for operations, decision making and planning. The Digital Group comprehends that the state of completeness, validity, consistency, timeliness and accuracy makes data appropriate for use. To achieve this level of conformity, data quality processes and the right technology needs to be implemented. T/DG follows some common methods to improve data quality. They are as follows:

  • Data Quality Analysis – Statistical Profiling, analysis of text and numeric fields, validation against standard patterns - email address syntax, credit card number formats or custom patterns
  • Data Standardization
  • Data Cleansing
  • Data De-duplication
  • Data Enrichment

Data Quality Dimensions

data quality process support and dimensions