Automated vs. Manual
ChoiceMED utilizes a custom-built, powerful web-based database application to automate the data cleansing, standardization and categorization process, as well as providing a Simple Object Access Protocol (SOAP) messaging layer for data synchronization and syndication.
The ChoiceMED technology platform is a robust environment that seamlessly integrates data quality within the data integration process, allowing our Data Analyst Team the ability for data profiling and rules creation through execution and monitoring of results. Our expert staff can then transform and combine disparate data, remove inaccuracies, standardize on common values, parse values and cleanse dirty data to create consistent, reliable information for your organization.
Rules can be built quickly while profiling data, and then incorporated automatically into the data transformation process. This speeds the development and implementation of cleansed data, as well as ongoing data management.
The ChoiceMED technology platform is a robust environment that seamlessly integrates data quality within the data integration process, allowing our Data Analyst Team the ability for data profiling and rules creation through execution and monitoring of results. Our expert staff can then transform and combine disparate data, remove inaccuracies, standardize on common values, parse values and cleanse dirty data to create consistent, reliable information for your organization.
Rules can be built quickly while profiling data, and then incorporated automatically into the data transformation process. This speeds the development and implementation of cleansed data, as well as ongoing data management.
Key Benefits
- Speeds the delivery of credible information by embedding data quality into batch and real-time processes.
- Reduces costly errors by preventing the propagation of bad data and correcting mistakes at the source.
- Keeps data current and accurate with regular auditing and cleansing.
- Standardizes data from multiple sources and reduces redundancy in corporate data to support more accurate reporting, analysis and business decisions.
- Adds value to existing data by generating and/or appending information from other sources.
- Data cleansing through a variety of techniques, including standardization, transformation and rationalization, while maintaining an accurate audit trail.
- Data profiling to identify incomplete, inaccurate or ambiguous data.
- Data enrichment and augmentation.
- Creates reusable data quality business rules that are callable through custom exits, message queues and Web services.
