Complex Aggregation at Multiple Granularities
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Selection of Views to Materialize in a Data Warehouse
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Maintaining Data Cubes under Dimension Updates
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Exploiting hierarchical clustering in evaluating multidimensional aggregation queries
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
Multiversion-based view maintenance over distributed data sources
ACM Transactions on Database Systems (TODS)
GPIVOT: Efficient Incremental Maintenance of Complex ROLAP Views
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Lazy maintenance of materialized views
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
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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.