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The construction sector has significantly evolved in recent decades, in parallel with a huge increase in the amount of data generated and exchanged in any construction project. These data need to be managed in order to complete a successful project in terms of quality, cost and schedule in the the context of a safe project environment while appropriately organising many construction documents.

However, the origin of these data is very diverse, mainly due to the sector’s characteristics. Moreover, these data are affected by uncertainty, complexity and diversity due to the imprecise nature of the many factors involved in construction projects. As a result, construction project data are associated with large, irregular and scattered datasets.

The objective of this chapter is to introduce an approach based on a fuzzy multi-dimensional model and on line analytical processing (OLAP) operations in order to manage construction data and support the decision-making process based on previous experiences. On one hand, the proposal allows for the integration of data in a common repository which is accessible to users along the whole project’s life cycle. On the other hand, it allows for the establishment of more flexible structures for representing the data of the main tasks in the construction project management domain. The incorporation of this fuzzy framework allows for the management of imprecision in construction data and provides easy and intuitive access to users so that they can make more reliable decisions.