A requirement-driven approach to the design and evolution of data warehouses

• We present a semi-automatic approach for an iterative design of MD schemas from a set of information requirements.
• We introduce novel algorithms for integrating MD schemata, each schema satisfying one or more requirements.
• Produced schemas are guaranteed to subsume all requirements, preserve the MD integrity constraints, and meet the user defined objectives.
• We introduce the traceability metadata to systematically record information about the best integration opportunities.
• We evaluate our approach by using a prototype and empirical tests which demonstrated the need for automated MD design.

Designing data warehouse (DW) systems in highly dynamic enterprise environments is not an easy task. At each moment, the multidimensional (MD) schema needs to satisfy the set of information requirements posed by the business users. At the same time, the diversity and heterogeneity of the data sources need to be considered in order to properly retrieve needed data. Frequent arrival of new business needs requires that the system is adaptable to changes. To cope with such an inevitable complexity (both at the beginning of the design process and when potential evolution events occur), in this paper we present a semi-automatic method called ORE, for creating DW designs in an iterative fashion based on a given set of information requirements. Requirements are first considered separately. For each requirement, ORE expects the set of possible MD interpretations of the source data needed for that requirement (in a form similar to an MD schema). Incrementally, ORE builds the unified MD schema that satisfies the entire set of requirements and meet some predefined quality objectives. We have implemented ORE and performed a number of experiments to study our approach. We have also conducted a limited-scale case study to investigate its usefulness to designers.