4.6. Data Quality
An integral part of TM is its ability to carry out various quality checks on source and desired target data. Inconsistent, incorrect, or redundant values in a dataset can be subjected to data quality/data cleansing techniques to bring it to a more consistent, accurate state.
Features which may be used to determine data quality include:
- XSD facet constraints may be applied to models regardless of model format, RDBMS, XML, or Java, and once defined, transforms can easily enforce these XSD Facet constraints.
- Many in-built data quality functions, for example check for date between range
- Data validation against full model constraints is enforced by default
- Reconciliation statements including tolerances set on values tested
- Error handling and logging allowing full control to respond to errors detected
4.7. Test and Debugger Tools
A Transformation Test Tool launched from the Design Tool, provides a run-time test tool to support interactive testing and development. Attaching test sources and running transforms to generate results quickly verify the transform’s statements.
Should more detailed analysis of the transform be required, a debugger permits the setting of breakpoints and stepping through transform statements to analyse transforms as they execute.
4.8. Deployment
TM is a code generator producing either Java code or XML transform descriptions, which can be run in a TM’s Java or .Net fixed run-time environment.
Generated Java code or Java fixed run-time environment can run on any Java Virtual Machine, and therefore integrate into a client architecture/application e.g. CRM, ERP, workflow, trading systems, messaging systems etc, whereas the .Net fixed run-time environment provides identical transform run-time features for the Microsoft architecture.
The Transformation Deployment Tool provides an easy-to-install Java application for scheduling and monitoring the progress of transforms. It provides access to transform status, progress, and logs that are generated.
