Abstract:

Advances in technologies, decreasing costs in massive storage, as well as a higher and faster access to available information along the Internet, are some of the factors involved in the existence of a current continuous stream of data that, properly stored and processed, can be later analysed to be applied in scenarios such as marketing strategies or decision support systems.

High volume, complexity, evolution along time, and heterogeneity in data sources are common features in this type of information, and appropriate structures are required. Data warehouses arise as a tool to integrate, store and properly manage this data. While traditional databases were designed to allow continuous and concurrent access to data by a large number of users, data warehouses are focused on organizing, analysing and retrieving data from a higher level in an organization or enterprise. Information is seen as an asset, and is structured by means of a multidimensional model, where each dimension contains a number of hierarchical features that allow the expert to analyse data at different detail levels.

The design of data warehouse is not a trivial stage, starting from the point that information must be collected from several, heterogeneous, data sources, and later pre-processed and integrated and stored into the data warehouse, as it has to be built according to the requirements and goals of the organization. Because of this, several commercial, as well as free, open source, software solutions are currently available to aid the user in the performing of these tasks. In this sense, it is very interesting to introduce Engineering students into this field of data analysis and information management.

This paper summarizes the educational experience, which took place between academic years 2013 and 2015 as part of a teaching innovation project, involving different courses and degrees in the University of Jaen (Spain). This experience has consisted of developing a practical experience to our students using a platform based on a multidimensional database model. This initiative has introduced the students in the different levels of information management considered in a data warehouse, in like manner as the information is processed in a real environment. This approach was followed taking into account two different courses competencies and profiles. Thus, we will analyse the differences between the experience performed on the students of the Degree in Computer Engineering, where it is crucial to be able to deal with the design and implementation of a data warehouse, and students in the Degree in Statistics and Business where the development of strategies or performance policies regarding information retrieved from the data warehouse is more relevant to the development of their professional skills.

Keywords:

Data warehousing, information management technologies, business intelligence, computational statistics.