Data Quality Assurance

It is the process of data profiling to discover inconsistencies and other anomalies in the data, as well as performing data cleansing activities (e.g. removing outliers, missing data interpolation) to improve the data quality.

Any and every data collected and interpreted by an organization must fulfill various characteristics in order to be useful and helpful in achieving various business objectives. ODA helps its clients in meeting these pillars of quality and assuring a more reliable approach to data handling.

Pillars of QA

  • Accuracy
  • Relevance
  • Correctness
  • Completeness
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