Hierarchy-Based Update Propagation in Decision Support Systems

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 domain, some methods propagate updates in hierarchies when data sources are subject to modifications. However, very few works have been performed so far regarding update propagation from summaries to data sources. This paper proposes an algorithm named PAM algorithm, to efficiently propagate modifications on summaries. Experiments on an operational application (Anticipeo) have been performed to validate our algorithm.