Data quality tools are designed to enhance the accuracy, completeness, relevance and consistency of a company’s data. Most tools fall into four general categories:
- Data Cleansing (or scrubbing)
- Data Auditing
- Data Migration
- Data integration
Some will focus on one category, but as data analytics technology matures, cross-functional solutions are becoming more common. Data quality informs many cross-functional elements of an organisation including master data management and meta data management, and the best tools for your task are determined by your case’s specific needs. you choose a data quality solution, you will need to understand which of these areas you need to focus on.
Of the many software providers, most offer specific capacities;
– data integrity and data cleansing tools
– drag-and-drop graphical interface
– near real-time synchronisation of data
– merging of duplicate records
– deduplicating import files
– measurement of performance against internal or external metrics and standards
With advances in AI capabilities, based on semantic technology data quality tools make use of semantic discovery and built-in pattern recognition and can automate repeatable tasks on a scheduled basis.