add share buttons

What does the Data Quality Assessment (DQA) mean?

  • June 28, 2019

Data quality assessment (DQA) is the process of evaluating data scientifically and statistically to determine whether they meet the quality needed for a business project or process and of the right type and amount to truly support the intended use.

It can be considered a set of guidelines and techniques used to describe data, provide an application context, and to implement processes to assess and improve data quality. If you want to know more about data quality assessment, you can browse

Data quality assessment (DQA) presents problems with technical and business data that allow organizations to properly plan data cleaning and enrichment strategies.

This is usually done to maintain system integrity, quality assurance standards, and compliance issues. In general, technical quality problems such as inconsistent structures and standard problems, missing data or default data are lost, and errors in the data field are easily recognized and corrected, but more complex problems must be approached with a clearer process.

Data Audit

DQA is usually done to correct subjective problems related to business processes, such as making accurate reports, and to ensure that processes that are driven by data and rely on data work as expected.

The DQA process is aligned with best practices and a set of prerequisites and with five dimensions of data quality:

  • Accuracy and reliability
  • Ability to serve
  • Accessibility
  • Methodological health
  • Integrity guarantee

Josep Lee

E-mail :