Search request
Press Enter to search and Esc to exit.
Unidata Data Quality
Unidata Data Quality (DQ – Data Quality). A product for ensuring the data quality of the enterprise. It allows you to create quality management processes based on integrated indicators, business rules and metrics. It has the ability to intelligently analyze the quality, detect patterns or deviations. It allows you to apply the developed quality rules in external information systems. Data quality rules can be configured both at the level of meta-information about the data structure and at the level of business entities.
The Unidata Data Quality product is used when storing data in the classic version in an MDM product is not practical due to their large number and constantly changing structure. We are talking about transactional data, reports, user information.
Phases of quality assurance

  • Data filtering
  • Data validation
  • Data cleaning
  • Consistency check
  • Enrichment from internal and external sources

Quality function

  • A software component that transforms input data into output data
  • Built-in – a set of standard data cleaning functions
  • Third-party – the ability to develop and connect a third-party function
  • Composite – Building new functions as compositions of existing functions

Quality rules

  • Implementation of the data quality function on the attributes of the registry or directory
  • Scripting – writing quality functions based on Groovy
  • External – using external SOAP & REST services

Data Quality – Opportunities

  • Storage and classification of found errors. Possibility of expanding the classification
  • Filtering and displaying records with errors in the user interface
  • Export of detected errors with data