Relational database reverse engineering: algorithms to extract cardinality constraints
Data & Knowledge Engineering
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Algorithm 447: efficient algorithms for graph manipulation
Communications of the ACM
Reconciling requirement-driven data warehouses with data sources via multidimensional normal forms
Data & Knowledge Engineering
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
ER'07 Proceedings of the 26th international conference on Conceptual modeling
Multidimensional design by examples
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
MDA transformations applied to web application development
ICWE'05 Proceedings of the 5th international conference on Web Engineering
Analyzing demographic and economic simulation model results: a semi-automatic spatial OLAP approach
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
GrHyMM: a graph-oriented hybrid multidimensional model
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
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Facts are multidimensional concepts of primary interests for knowledge workers because they are related to events occurring dynamically in an organization. Normally, these concepts are modeled in operational data sources as tables. Thus, one of the main steps in conceptual design of a data warehouse is to detect the tables that model facts. However, this task may require a high level of expertise in the application domain, and is often tedious and time-consuming for designers. To overcome these problems, a comprehensive model-driven approach is presented in this paper to support designers in: (1) obtaining a CWM model of business-related relational tables, (2) determining which elements of this model can be considered as facts, and (3) deriving their counterparts in a multidimensional schema. Several heuristics -based on structural information derived from data sources- have been defined to this end and included in a set of Query/View/Transformation model transformations.