
DATA QUALITY
Opportunities for improving data quality

Quality in data, quality in information

When starting a Data Quality process we follow the following steps:
Requirements gathering:
Data profile identification:
Identification of associated flows:
Implementation:
Integrity: The use of primary and foreign keys assumes a crucial role in the case of relational bases, in situations of multiple unrelated systems we ensure the existence of validation of additional conditions to the format (check constraint) and the use of mechanisms triggered by specific actions (triggers).
Traceability: Whenever a problem is detected in a log, we guarantee that it is possible to quickly identify its origin and correct it.
Completeness: If necessary, the process may include crossing with external data sources, enriching the data and generating information with great potential..
Meet the rest of the family

Data Converter

Data integrator

Data Quality

Data Reader
