Data mastership

Businesses often use multiple tools to manage project information. Data mastership is the mapping of these several disparate projects to a single, common entity. The sample catalog defines a framework for simplifying the ETL implementation for data mastership.
If you use RequisitePro® to manage requirements, ClearQuest® to manage change requests, and ClearCase® to manage source code you can map the RequisitePro project, some examples of data mastership are:

Implementation of data mastership through the XML data configuration files

Dimension mapping tables are used for defining the rules to map dimensions from one data source to another. Dimension mapping tables are of two types: Dimension mapping tables can be grouped into dimension mapping categories. If you use yours resource group categories to group data sources with the same data structure, you can also use dimension mapping category to group dimension mapping tables defined for the same common dimension. The ETL jobs can query the dimension mapping tables associated with the category and load all mapping information automatically.

When defining the mappings in XML data configuration files, you query information from the XML ODBC driver. The system table System.DIMENSIONMAPPINGS can be used to query information about available dimension mapping tables. All dimension mapping tables are under the schema DimensionMappings. All tables have the same structure, that is, a source_value and a target_value. They can be used to query the value mappings.

Implementation of data mastership in the ETL process

In the data warehouse artifacts for the common dimension, only those artifacts that behave as the master (target of the mapping) or those artifacts that are not mapped to any other artifacts appear in the operational data store. Other artifacts that are associated with the common dimension are linked to the target artifact of the original artifact directly. For example, if a UCM Project RI is mapped to a ClearQuest project Insight, only the ClearQuest project Insight appears in the PROJECT table, and the UCM activities belong to the UCM project RI will be directly linked to the ClearQuest project Insight in the data warehouse. For each of the common dimensions, including PROJECT, RELEASE, ITERATION, PRODUCT, COMPONENT and RESOURCE, staging mapping tables with M_ prefixed to their names are created as tables used in ETL to store the mapping relationship.

The ETL data flow to build data mastership is:

Data mastership involves multiple data sources. Therefore, the ETL job must reflect the overall data flow. The above implementation for data mastership is specific to the ETL process and has no impact on other components. In the sample catalog, a TestManager project is mapped to a ClearQuest ALM project, and TestManager users to ClearQuest ALM users with the same name. If you see errors when opening the XML data configuration file for TestManager ETL, update the dimension mapping tables to point to the XML data configuration file used for ClearQuest ETL in your system.


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