Design Staging Tables and Data Extraction Processes
Quickly define Staging tables and Extract processes by connecting to and importing table and column Meta Data from your source systems. Many different connection sources are supported. Column mapping between source and staging tables can defined for Extract code generation. Supports complex query sources, expressions, custom Meta data and derived table creation for more complex Extract requirements.
Design Facts, Dimensions and Transformation/Load Processes
DW Architect allows you to design Facts and Dimensions.
Define dimension business keys and attributes including attribute descriptions, data types, slowly changing types, parent settings etc. Define custom surrogate key data types and names, and custom meta data for more complex design requirements.
Design fact tables and their dimensionality in the data warehouse. Define measures, their data type and description. Associate the Fact with the dimensions defined in the project. DW Architect caters for Role play names, Many to Many dimensions and conforming dimensions from other Data Marts.
Define Transform and Load Meta Data with Staging to Dimension attribute mapping, ETL patterns, Matching criteria, Filters, Expressions etc.
Generate
DW Architect includes a code generation platform to generate the required code from Meta Data defined in the Design Environment. The platform includes a user interface, engines and templates to generate the entire suite of Data Warehouse and ETL code artefacts required to implement your data warehouse. The code can be generated through the management console or by command line. The code generation platform is extensible allowing you to develop your own templates, and generation engine providers.
Included are templates and engines to generate:
- Staging Tables DDL synchronization.
- Data Warehouse Tables DDL synchronization.
- Extract, Transform and Load (ETL) procedures.
- Table Management procedures.
- Data Dictionary.
Included Engines are:
- XSLT generation Engine. Create XSLT templates to generate code from ‘DW Architect’ Meta Data.
It is important that data is not destroyed, when the Data Warehouse schema is updated. Existing schema synchronisation tools implement a column name change as a drop and create column pair destroying data in the existing column as they do so.
DW Architect advanced DDL generation methods preserves data, recognizes name changes, and generates scripts which test the existing state of your data warehouse, creating and modifies tables and columns as required.