Tracing conceptual models' evolution in data warehouses by using the model driven architecture

• A set of semantic traces to support conceptual traceability in data warehouses
• Simplifies analysis of the impact of changes and integration of data and new sources
• Includes a set of rules based on the QVT standard for deriving the data warehouse
• We apply our proposal to create an education data mart.

Developing a data warehouse is an ongoing task where new requirements are constantly being added. A widely accepted approach for developing data warehouses is the hybrid approach, where requirements and data sources must be accommodated to a reconciliated data warehouse model. During this process, relationships between conceptual elements specified by user requirements and those supplied by the data sources are lost, since no traceability mechanisms are included. As a result, the designer wastes additional time and effort to update the data warehouse whenever user requirements or data sources change. In this paper, we propose an approach to preserve traceability at conceptual level for data warehouses. Our approach includes a set of traces and their formalization, in order to relate the multidimensional elements specified by user requirements with the concepts extracted from data sources. Therefore, we can easily identify how changes should be incorporated into the data warehouse, and derive it according to the new configuration. In order to minimize the effort required, we define a set of general Query/View/Transformation rules to automate the derivation of traces along with data warehouse elements. Finally, we describe a CASE tool that supports our approach and provide a detailed case study to show the applicability of the proposal.