By Ladjel Bellatreche, Mukesh K. Mohania
This ebook constitutes the refereed court cases of the sixteenth foreign convention on info Warehousing and information Discovery, DaWaK 2014 held in Munich, Germany, September 2014, at the side of DEXA 2014. The 34 revised complete papers and eight brief papers awarded have been conscientiously reviewed and chosen from 109 submissions. The papers are prepared in topical sections on modeling and ETL; ontology-based facts warehouses; complicated facts warehouses and OLAP; uncertainty; personal tastes and advice; question functionality and HPC; dice & OLAP; optimization; class; social networks and advice structures; wisdom info discovery; commercial functions; mining and processing information move; mining and similarity.
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Additional resources for Data Warehousing and Knowledge Discovery: 16th International Conference, DaWaK 2014, Munich, Germany, September 2-4, 2014. Proceedings
Adaptability: the degree to which ETL process can eﬀectively and eﬃciently be adapted for diﬀerent operational or usage environments. It includes: (a) scalability: the ability of the ETL process to handle a growing demand, regarding both the size and complexity of input data and the number of concurrent process users. , by automatically switching endpoints). M1: # of precedence dependences between activities  (−) (c) reusability: the degree to which components of the ETL process can be used for operations of other processes.
The approach is exemplified through a real scenario of the Brazilian electrical system, supporting the joint exploration of electrical disturbances data and their possible repercussion on the news. Keywords: Business Intelligence, Multidimensional Design, Conceptual Modelling, Foundational Ontologies. 1 Introduction The MD design task is a fundamental core phase in the Data Warehousing (DW) lifecycle  and BI solutions, requiring an engineering process to capture semantics from business entities and their relations.
1471–1472. IEEE (2007) 11. : Schema versioning and database conversion techniques for bi-temporal databases. Annals of Mathematics and Artiﬁcial Intelligence 30(1-4), 23–52 (2000) 12. : Metadata management in a multiversion data warehouse. , et al. ) Journal on Data Semantics VIII. LNCS, vol. 4380, pp. 118–157. Springer, Heidelberg (2007) 13. : Managing and querying versions of multiversion data warehouse. , et al. ) EDBT 2006. LNCS, vol. 3896, pp. 1121– 1124. br Abstract. The choice on information representation is extremely important to fulfil analysis requirements, making the modelling task fundamental in the Business Intelligence (BI) lifecycle.
Data Warehousing and Knowledge Discovery: 16th International Conference, DaWaK 2014, Munich, Germany, September 2-4, 2014. Proceedings by Ladjel Bellatreche, Mukesh K. Mohania