Computer
On the semantics of “now” in databases
ACM Transactions on Database Systems (TODS)
Materialized views: techniques, implementations, and applications
Materialized views: techniques, implementations, and applications
Equivalence of Relational Algebra and Relational Calculus Query Languages Having Aggregate Functions
Journal of the ACM (JACM)
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Efficient integration and aggregation of historical information
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
A foundation for vacuuming temporal databases
Data & Knowledge Engineering
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Managing Aging Data Using Persistent Views (Extended Abstract)
CooplS '02 Proceedings of the 7th International Conference on Cooperative Information Systems
PVS: Combining Specification, Proof Checking, and Model Checking
CAV '96 Proceedings of the 8th International Conference on Computer Aided Verification
VLDB '80 Proceedings of the sixth international conference on Very Large Data Bases - Volume 6
Gradual data aggregation in multi-granular fact tables on resource-constrained systems
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
Using a time granularity table for gradual granular data aggregation
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Schema design alternatives for multi-granular data warehousing
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
A rule-based tool for gradual granular data aggregation
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
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Many data warehouses contain massive amounts of data, accumulated over long periods of time. In some cases, it is necessary or desirable to either delete ''old'' data or to maintain the data at an aggregate level. This may be due to privacy concerns, in which case the data are aggregated to levels that ensure anonymity. Another reason is the desire to maintain a balance between the uses of data that change as the data age and the size of the data, thus avoiding overly large data warehouses. This paper presents effective techniques for data reduction that enable the gradual aggregation of detailed data as the data ages. With these techniques, data may be aggregated to higher levels as they age, enabling the maintenance of more compact, consolidated data and the compliance with privacy requirements. Special care is taken to avoid semantic problems in the aggregation process. The paper also describes the querying of the resulting data warehouses and an implementation strategy based on current database technology.