This paper proposes and discusses a GIS that integrates geographic resources with business intelligence data from SAP/R3 and BW. The latter includes stores and wholesalers’ data, daily updated by an automated process of extraction from BW, geocoding and spatial related attribute processing. It has a simple interface that makes service provider contract management and analysis easier. Standard map functionalities are available. The most relevant functionalities are map queries used as OLAP queries filter and the joining of BW queries and map features, enabling spatial analysis or thematic maps’ creation over the SAP data.

Given its scope for flexibility, scalability reliability and customisation, it is no surprise that GIS has found its way into a variety of professions and spawned a whole range of applications. Most of these applications demand that geographic data be integrated with business data. Usually, the former is added to the latter for map publishing or analysis using geographic tools and techniques (spatial analysis, geostatistical analysis etc). A few years ago, new data warehouse systems were developed based on relational technology to store tactical information to help make better decisions. However, these systems were limited in the sense that they answered only questions like who, when, what and how much. Advances in technology (both hardware and software) resulted in the development and application of more powerful tools for Online Analytical Processing (OLAP). OLAP uses multi-dimensional raw data aggregated and summarised to generate business intelligence reports providing interactive access to a wide variety of possible views of information (OLAP Council 1997).

GIS software is easier than OLAP systems but its reach is still limited.

Objective
To present a simple yet powerful method using which business analysts can add spatial data to their analysis.

GIS data integration and OLAP
A database is itself a kind of an application wherein data related to real objects or events is stored. Linking such table rows with spatial features is the best way to introduce GIS into the business world. Data integration between spatial and business databases is a simple and quick way to successfully obtain maximum benefit from any investment on GIS. Most databases can easily be accessed by standard components like Microsoft OLE DB. In fact, most of the GIS products come with database access capabilities.

Like databases, OLAP systems store data but in a different way and for different purposes. Usually, data is related to multiple characteristics like a date, place, salesman, customer etc. In other words, raw data belongs to a very specific element in a few varieties of dimensions of the available data universe. For instance, if the total sales of a cookie brand at a downtown store amounted to US$ 1250 on 7/5/2002, we have three dimensions (product, geography and time) and one variable (sale volume in dollars). This kind of raw sales data is stored for all products, at all stores and on all days.

The data in an OLAP system is stored in a special structure known as cube. In diagram 2, it even looks like a cube as it just mixes three dimensions. However, multi-dimensional data can be related to an infinite number of dimensions.