The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
Data Warehousing Fundamentals
Robust and efficient fuzzy match for online data cleaning
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A fuzzy-based decision-making procedure for data warehouse system selection
Expert Systems with Applications: An International Journal
Fuzzy Spatial Data Warehouse: A Multidimensional Model
ENC '07 Proceedings of the Eighth Mexican International Conference on Current Trends in Computer Science
A Fuzzy Data Warehouse Approach for Web Analytics
WSKS '09 Proceedings of the 2nd World Summit on the Knowledge Society: Visioning and Engineering the Knowledge Society. A Web Science Perspective
SQLf: a relational database language for fuzzy querying
IEEE Transactions on Fuzzy Systems
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Fuzzy Data Warehouse (FDW) is a data repository, which contains fuzzy data and allows fuzzy processing of the data. Incorporation of fuzziness into data warehouse systems gives the opportunity to process data at higher level of abstraction and improves the analysis of imprecise data. It also gives the possibility to express business indicators in natural language using terms, like: high, low, about 10, almost all, etc., represented by appropriate membership functions. Fuzzy processing in data warehouses can affect many operations, like data selection, filtering, aggregation, and grouping. In the paper, we concentrate on various cases of data aggregation in our recently implemented fuzzy data warehouse storing consumption and requirement for global natural resources represented as crisp and fuzzy measures. We show several examples of data aggregation and filtering using the extended syntax of the SQL SELECT statement.