Sales forecasting systems are used by enterprise managers and executives to better understand the market trends and prepare appropriate business plans. These decision support systems usually use a data warehouse to store data and OLAP tools to visualize query results. A specific feature of sales forecasting systems regarding future predictions modification is backward propagation of updates, which is the computation of the impact of modifications on summaries over base data. In Data warehouses, some methods propagate updates in hierarchies when data sources are subject to modifications. However, very few works have been devoted so far, regarding update propagation from summaries to data sources. This paper proposes an algorithm called PAM (Propagation of Aggregate Modification), to efficiently propagate modifications on summaries over base data. Experiments on an operational application (Anticipeo) have been conducted.
Cette présentation sera donnée à DASFAA'12
http://db.pknu.ac.kr/dasfaa2012/index.php?menu=papers#in2
