Spatial data warehouse or spatial data warehouse is a collection of subject-oriented, integrated, non-volatile, time-varying data that adds the geography of data, for decision making.
However, the geographical component is not an aggregate data, but rather a dimension or variable in information technology, in such a way that it allows modeling the entire business as a holistic entity, and that through online analytical processing tools ( OLAP), not only does it have a high performance in multidimensional queries, but also the results can be visualized spatially.
The Spatial Data Warehouse forms the heart of an extensive Geographic Information System for decision making, this, like GIS, allows a large number of users to access integrated information, unlike a simple Data Warehouse that is oriented To the topic, the spatial data warehouse is additionally Geo-Relational, that is to say that in relational structures it combines and integrates the spatial data with the descriptive data. Currently it is Geo-Objects, that is, geographic elements manifest as objects with all their properties and behaviors, and that are additionally stored in a single Object-Relational database.
Spatial Data Warehouses are applications based on high-performance databases that use Client-Server architectures to integrate diverse data in real time. While data warehouses work with many types and dimensions of data, many of which do not refer to spatial location, despite having it intrinsically, and knowing that 80% of the data has representation and location in space, in spatial data warehouses , the geographic variable plays an important role in the information base for the construction of the analysis, and just as for a data warehouse, the time variable is essential in the analysis, for spatial data warehouses the geographic variable must be stored directly in her.