Human Inference offers a total solution that covers all dimensions of data quality from an integrated point of view. All the solutions can be implemented on-line or in batch. This not only enables efficient initial cleansing but also allows for pollution prevention at the source. The HIquality platform comprises the following functional elements.
HIquality Studio
HIquality® Studio facilitates user-, knowledge-, system-, and process-management and reporting. It also features
HIquality® Composer, a graphical toolkit for designing and testing data quality services based on predefined and customized building blocks.
For more information click here to download the fact sheet.
HIquality Base
HIquality Base forms the solid foundation of the HIquality Product Suite. This is where the business service plug-ins deliver their services, and interface connectors provide interaction and data exchange between the platform and external business applications. HIquality Base takes care of message handling between interface connectors and business service plug-ins, logging, security, and process monitoring.
Business Service Plug-ins
The realization of the various phases of the Data Quality Life Cycle is achieved through so-called business service plug-ins. The interface is made available to the public domain, which means every organization using the platform can add its own custom-built or third party plug-ins. This enables the use of the Human Inference proposition as the central platform for data quality.
Interface Connectors
For a wide range of protocols, interface connectors are available. In addition, integration with the CRM, BI, and ERP applications of most other major vendors is provided for.
HIquality Dashboard
A rule-base engine provides the link between the business service plug-ins. It triggers the services and combines business service plug-ins into a function at the application level.
The dashboard is the central point of control for data quality. It enables end-users like Database Marketeers, Database Analysts and List Managers to process data without or with very little programming effort. This allows for a step-by-step approach to set up a cleansing process, starting with measurement of the data and ending up with reporting on actions taken.
 Print this page
|
