An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
A general framework for the view selection problem for data warehouse design and evolution
Proceedings of the 3rd ACM international workshop on Data warehousing and OLAP
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Essential Oracle8i Data Warehousing: Designing, Building, and Managing Oracle Data Warehouses (with Website)
Multiple View Consistency for Data Warehousing
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Selection of Views to Materialize Under a Maintenance Cost Constraint
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Reasoning about Summarizability in Heterogeneous Multidimensional Schemas
ICDT '01 Proceedings of the 8th International Conference on Database Theory
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Extending Practical Pre-Aggregation in On-Line Analytical Processing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Changes of Dimension Data in Temporal Data Warehouses
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Consistency in Data Warehouse Dimensions
IDEAS '02 Proceedings of the 2002 International Symposium on Database Engineering & Applications
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Supporting Imprecision in Multidimensional Databases Using Granularities
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Multidimensional Data Modeling for Complex Data
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Maintaining Data Cubes under Dimension Updates
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Capturing summarizability with integrity constraints in OLAP
ACM Transactions on Database Systems (TODS)
STORM: a statistical object representation model
SSDBM'1990 Proceedings of the 5th international conference on Statistical and Scientific Database Management
Consistent query answering in databases
ACM SIGMOD Record
OLAP over uncertain and imprecise data
The VLDB Journal — The International Journal on Very Large Data Bases
Hierarchies in a multidimensional model: from conceptual modeling to logical representation
Data & Knowledge Engineering - Special issue: WIDM 2004
Exploiting versions for on-line data warehouse maintenance in MOLAP servers
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Improving data quality: consistency and accuracy
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Conditional functional dependencies for capturing data inconsistencies
ACM Transactions on Database Systems (TODS)
A survey on summarizability issues in multidimensional modeling
Data & Knowledge Engineering
Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems
Data & Knowledge Engineering
Repairing dimension hierarchies under inconsistent reclassification
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
Repairing inconsistent dimensions in data warehouses
Data & Knowledge Engineering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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A dimension in a data warehouse (DW) is an abstract concept that groups data that share a common semantic meaning. The dimensions are modeled using a hierarchical schema of categories. A dimension is called strict if every element of each category has exactly one ancestor in each parent category, and covering if each element of a category has an ancestor in each parent category. If a dimension is strict and covering we can use pre-computed results at lower levels to answer queries at higher levels. This capability of computing summaries is vital for efficiency purposes. Nevertheless, when dimensions are not strict/covering it is important to know their strictness and covering constraints to keep the capability of obtaining correct summarizations. Real world dimensions might fail to satisfy these constraints, and, in these cases, it is important to find ways to fix the dimensions (correct them) or find ways to get correct answers to queries posed on inconsistent dimensions. A minimal repair is a new dimension that satisfies the strictness and covering constraints, and that is obtained from the original dimension through a minimum number of changes. The set of minimal repairs can be used as a tool to compute answers to aggregate queries in the presence of inconsistencies. However, computing all of them is NP-hard. In this paper, instead of trying to find all possible minimal repairs, we define a single compatible repair that is consistent with respect to both strictness and covering constraints, is close to the inconsistent dimension, can be computed efficiently and can be used to compute approximate answers to aggregate queries. In order to define the compatible repair we defined the notion of extended dimension that supports sets of elements in categories.