Business Intelligence and its Applications to the Public Administration

Journal Title: Journal of Business Management and Applied Economics - Year 2012, Vol 1, Issue 1

Abstract

Data which have been filtered and analyzed, in order to produce a synthetic, structured and meaningful set of information - made available for strategic decision making - are put under the broad definition of intelligence. Business Intelligence (BI) consists in gathering intelligence from corporate data. It is a complex process, including many components and functions. The basic ones are: On-line Transaction Processing (OLTP), data warehousing, On Line Analytical Processing (OLAP) and data mining. OLTP is the process of extracting data from a transactional database. OLTP results can be sets of records or statistical indicators like means and standard deviations. A data warehouse is a multi-dimensional data storage facility. Data warehouses allow performing OLAP: fast analysis of shared multidimensional information. Data mining is a powerful technique for knowledge discovery, based on statistical algorithms. Its aim is to find hidden patterns and models (associations, correlations etc.), together with counter-intuitive information. The Italian administration has recently adopted a Business Intelligence system to measure its efficiency. The system relies on the measurability of results, comparing them to the expected output. Lower-than-expected efficiency may result in increased auditing and eventual penalization. Good or excellent performances may instead be rewarded. Different projects have been undertaken in order to prevent or detect frauds, especially in the fiscal and financial areas. Predictive modelling may improve auditing efficiency, reducing the costs related to useless audits and increasing the probability of effective ones.

Authors and Affiliations

Davide Barbieri

Keywords

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  • EP ID EP114154
  • DOI -
  • Views 94
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How To Cite

Davide Barbieri (2012). Business Intelligence and its Applications to the Public Administration. Journal of Business Management and Applied Economics, 1(1), 1-10. https://europub.co.uk/articles/-A-114154