Our experts are well versed in industry best practices such as ISO 8000, the international standard for data quality, & International Association for Information & Data Quality (IAIDQ) standards.
What We Cover
- Data Profiling: Assessing the data to understand it’s quality challenges
- Data Standardization: Ensuring that data conforms to quality rules, sometimes through a business rules engine.
- Matching & Linking: Comparing data so that similar, but slightly different, data items or records can be aligned appropriately. Matching may use “fuzzy logic” to find duplicate data and build a “best of breed” record, taking the best components from multiple data sources and building a single record.
- Monitoring: Keeping track of data quality over time and reporting variations in the quality of data or auto-correcting it based on pre-defined business rules.
- Batch & Real-time: Once the data is cleansed, agencies or companies wanting to build the processes into enterprise applications will be able to keep it clean.