A model for a library‐management toolbox: Data warehousing as a tool for filtering and analyzing statistical information from multiple sources

Quality management, and its associated evidence‐based ideology, have influenced library management from at least the beginning of the 1990s. Both concepts emphasize that decisions have to be based on facts. Libraries have a long history of using statistics in data collection due to international agreements and standards. Although there is much data available in the libraries, perhaps this collected data have not been utilized as effectively as possible. This paper aims to discuss the possibilities of combining different types of statistical data in order to measure the efficiency of the work being done in libraries and what possible impact they can have in their parent organizations. It also aims to use the concept of data warehousing as a tool for joining different types of statistical data in the analysis.

This paper is a case study with statistical analysis of library data collected and a conceptual analysis of possibilities in the data warehousing of the library and library‐related data in order to improve its analysis.

The authors suggest that in order to improve the analysis of the library statistical data towards the actual effects the library has, for example, to the learning and research done within university, one must start to develop statistical data systems that enable the combination of different types of statistical data. This needs co‐operation between different vendors and government officials in defining the statistical data collected.

The paper is based on Finnish experiences and the data warehousing model should be tested empirically and developed further due to the challenges in the conformity of the data collected.

The paper presents ideas and possibilities to evolve the library statistical data analysis.

The paper presents ideas for national and international bodies in how to develop statistical data systems and their interoperability.

The paper promotes the idea of combining library and other statistical data collected in order to provide better tools for library management.