The aggregate data problem: a system for their definition and management
ACM SIGMOD Record
OLAP and statistical databases: similarities and differences
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
starER: a conceptual model for data warehouse design
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
On the content of materialized aggregate views
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
On relationships offering new drill-across possibilities
Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Normal Forms for Multidimensional Databases
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Reconsidering Multi-Dimensional schemas
ACM SIGMOD Record
An analysis of additivity in OLAP systems
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
Solving summarizability problems in fact-dimension relationships for multidimensional models
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
A survey on summarizability issues in multidimensional modeling
Data & Knowledge Engineering
Ontologies and summarizability in OLAP
Proceedings of the 2010 ACM Symposium on Applied Computing
Improving the development of data warehouses by enriching dimension hierarchies with WordNet
ODBIS'05/06 Proceedings of the First and Second VLDB conference on Ontologies-based databases and information systems
Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems
Data & Knowledge Engineering
Enforcing strictness in integration of dimensions: beyond instance matching
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
Enriching data warehouse dimension hierarchies by using semantic relations
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
Benchmarking summarizability processing in XML warehouses with complex hierarchies
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Detecting summarizability in OLAP
Data & Knowledge Engineering
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Accurate summarizability is an important property in OLAP systems because inaccurate summaries can result in poor decisions. Furthermore, it is important to understand and identify the potential sources of inaccurate summaries. In this paper, we present a taxonomy of inaccurate summary factors and practical rules for handling them. We consolidate relevant terms and concepts in statistical databases with those in OLAP systems and explore factors that are important for measuring the impact of erroneous summaries. We discuss these issues from the perspectives of schema, data, and computation. This paper contributes to a comprehensive understanding of summarizability and its impact on decision-making. Our work could help designers and users of OLAP systems reduce unnecessary constraints caused by imposing rules to eliminate all summarizability violations and give designers a means to prioritize problems.