Data warehouses are IT systems which are characterized by a particular manner of recording and presenting data. What’s particular is that data collected within a database is recorded in the form in which it appears in reports. It involves deriving data from its source system form, whereby single business events (e.g. single order) are the most important, as well as converting it to the processed form, whereby the main item is (e.g. the sales record of a product). The difference seems slight, however, from the point of view of users who analyze data, and in terms of access to data, it is a revolutionary change.

The need for implementation of data warehouse is common – it concerns large corporations as well as small and medium enterprises. It stems from the fact that data warehouse constitutes a strategy of collecting and analyzing cross-sectional data pertaining to numerous aspects of organization activity linked together.

BAKK presents the manner of implementing a data warehouse with low costs and the utmost focus on return on investment period.

It would be difficult to describe the benefits of data warehouse without referring to a broader business context and solutions available on the market – therefore, we present a business justification for data warehouse profitability as well as alternative architectures to be applied.

Notions used by BAKK in the scope of data warehouse: data warehouse, data marts, data cubes, MIS (Management Information System), DSS (Decision Supporting System), BI (Business Intelligence), multidimensional data structures, dimensions, measures, hierarchies etc.