Data Modelling
Data modelling is essential for transforming raw information into usable structures that reflect organisational needs. By mapping business concepts into structured forms, it provides analysts with the clarity required to ensure reliable insights and support effective decision-making (Teorey et al., 2011).
Technique Overview
Data Modelling Definition
Data modelling is the structured process of representing data objects, relationships, and rules to support organisational information systems. It spans conceptual (business-focused), logical (system-independent), and physical (platform-specific) levels (Batini, Lenzerini & Navathe, 1986; Teorey et al., 2011; Atzeni, Cabibbo & Torlone, 2018). Using notations such as ER diagrams, UML, or dimensional schemas, it defines tables, keys, and cardinalities that ensure clarity, consistency, and analytical value (Chen, 1976; Ballard et al., 1998; Bavota et al., 2011).
Data Modelling Description *
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Business Evidence
Strengths, weaknesses and examples of Data Modelling *
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Business Application
Implementation, success factors and measures of Data Modelling *
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Professional Tools
Data Modelling videos and downloads *
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Further Reading
Data Modelling web and print resources *
Data Modelling references (4 of up to 20) *
- Ballard et al. (1998) Data modeling techniques for data warehousing (p. 25). San Jose: IBM Corporation International Technical Support Organization. available at: http://eddyswork.synthasite.com/resources/Data%20Modeling%20Tech%20For%20Data%20Warehouseing.pdf
- Atzeni, P., Cabibbo, L., Torlone, R. (2018). Data Modeling Across the Evolution of Database Technology. In: Flesca, S., Greco, S., Masciari, E., Saccà, D. (eds) A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years. Studies in Big Data, vol 31. Springer, Cham.
- Batini, C., Lenzerini, M. and Navathe, S.B. (1986). A comparative analysis of methodologies for database schema integration. ACM Computing Surveys, 18(4), pp.323–364. doi:https://doi.org/10.1145/27633.27634.
- Bavota, G. et al. (2011). Identifying the Weaknesses of UML Class Diagrams during Data Model Comprehension. In: Whittle, J., Clark, T., Kühne, T. (eds) Model Driven Engineering Languages and Systems. MODELS 2011. Lecture Notes in Computer Science, vol 6981. Springer, Berlin, Heidelberg.
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