- Our Services
- Industries
- Competencies
- Consulting
- Technology
- Application Development
- arvato IX Solutions
- Business Intelligence
- Cloud Computing
- Data Center Technology & Operations
- Data Management
- IBM Commerce Solutions
- Microsoft Business Solutions
- Network & Security
- Portal & Content Management
- Remote Desktop Solutions
- SAP Solutions
- Search Engine Optimization & Search Engine Marketing
- Service Oriented Architecture
- Software as a Services (SaaS)
- System Integration Solutions
- 3G Technology
- Outsourcing
- Consulting
- Industries
-
- Consulting
- Technology
-
- Application Development
- arvato IX Solutions
- Business Intelligence
- Cloud Computing
- Data Center Technology & Operations
- Data Management
- IBM Commerce Solutions
- Microsoft Business Solutions
- Network & Security
- Portal & Content Management
- Remote Desktop Solutions
- SAP Solutions
- Search Engine Optimization & Search Engine Marketing
- Service Oriented Architecture
- Software as a Services (SaaS)
- System Integration Solutions
- 3G Technology
- Outsourcing
Solution
Data Management - Data Cleansing and Integration
Definition of data quality problem is closely related to business area. Data that are clean to one department may be dirty to another department. Business changes over time, so definitions of data quality and integration problem change over time. Rules of data cleansing often become different. Customers need to define rules of data cleansing and integration flexibly and online.
Rule engine technology can solve the problem. Rule engine tests submitted data objects and compares them with existing rules to activate rules that meet current data status. The engine then triggers related operations according to execution logic of the rules. So, rule engine technology converts hard-coding and complex if…else… structure to soft-coding rule set. Customers can define and adjust rules flexibly.
