Spatial Data Warehouse design and data dissemination
Data Warehouses are in use to analyze large volumes of data. ETL is an established process of loading data into a Data Warehouse. For administrative DWH-designers, time, cubes and data marts are common technical concepts.
GIS systems are designed for operational tasks, not specifically to be used as a Data Warehouse. When implementing a Spatial Data Warehouse the following questions become relevant:
- How to structure spatial data for a DWH?
- How to design a spatial DWH answering a range of business questions?
- What business questions to expect?
- How to incorporate the time aspect?
- How to analyse spatial, temporal and administrative data in one go?
A large energy company uses Spatial Workshop to design and evaluate the integration of spatial data into their DWH environment.
Dynamic Spatial DataWarehouse
Organizations collect increasingly significant volumes of data. Once stored in data warehouses, they form the basis for data analysis processes and guide the organization's strategic decisions.
However, the available data is not always used to their full potential and part of their richness is simply left out, that is, their spatial component. Hidden in most data is a geographical component that can be tied to a place: an address, postal code, global positioning system location, (…) region or country. Indeed, it has been estimated that about eighty percent of all data stored in corporate databases has a spatial component [Franklin 1992] that can be characterized by position, shape, orientation or size.
Time may also be a central component of data: "...without a record of the time of the observation, the useful content of the information may be minimal" [Sinton 1978]. The importance of the temporal dimension for decision making is crucial. Spatial dimensions, just like temporal ones, will be increasingly considered standard for any data warehouse implementation.
Spatial Workshop and Spatial Data Warehouse technology
Spatial OLAP can be defined as a visual platform built especially to support rapid and easy spatiotemporal analysis and exploration of data following a multidimensional approach comprised of aggregation levels available in cartographic displays as well as in tabular and diagram displays [Bédard 1997].
Spatial Workshop offers functionality that supports a stack of Data Warehouse functions in a spatial way.
- Spatial and administrative data can be integrated to added to the DWH,
- Data can be transformed (on the fly) in to Spatial Business Objects useful for the business,
- Data can be sliced, diced and prepared for specific business use (Data Marts),
- Spatial, administrative and temporal data can be analyzed, presented and reported in different ways.
The user may switch quickly and transparently between different forms of presentation.
One of the difficult aspects of creating a Spatial Data Warehouse is the fact that, in many cases, it is not clear what questions the business would like to ask to a Spatial Data Warehouse. Creating awareness of the potential of a Spatial Data Warehouses and evaluating the business requirements is a critical phase during the design of the Spatial Data Warehouse.
Spatial Workshop can, in many ways, be used as a dynamic Data Warehouse and thus support the design process for the actual Data Warehouse. The DWH designer can supply the users with easy to learn and flexible tools to define and evaluate their requirements.
