research-article

A Holistic Approach to OLAP Sessions Composition: The Falseto Experience

Authors:

Patrick Marcel,

Veronika PeraltaAuthors Info & Claims

DOLAP '14: Proceedings of the 17th International Workshop on Data Warehousing and OLAP

Pages 37 - 46

https://doi.org/10.1145/2666158.2666179

Published: 07 November 2014 Publication History

Abstract

OLAP is the main paradigm for flexible and effective exploration of multidimensional cubes in data warehouses. During an OLAP session the user analyzes the results of a query and determines a new query that will give her a better understanding of information. Given the huge size of the data space, this exploration process is often tedious and may leave the user disoriented and frustrated. This paper presents an OLAP tool named Falseto (Former AnalyticaL Sessions for lEss Tedious Olap), that is meant to assist query and session composition, by letting the user summarize, browse, query, and reuse former analytical sessions. Falseto's implementation on top of a formal framework is detailed. We also report the experiments we run to obtain and analyze real OLAP sessions and assess Falseto with them. Finally, we discuss how Falseto can be seen as a starting point for bridging OLAP with exploratory search, a search paradigm centered on the user and the evolution of her knowledge.

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Cited By

Yousaf AKhattak AKhan K(2021)Ontology Evolution Using Recoverable SQL LogsService-Oriented Computing – ICSOC 2020 Workshops10.1007/978-3-030-76352-7_46(509-517)Online publication date: 30-May-2021
https://doi.org/10.1007/978-3-030-76352-7_46
Alvarez-Ayllon APalomo-Duarte MDodero J(2019)Interactive Data Exploration of Distributed Raw Files: A Systematic Mapping StudyIEEE Access10.1109/ACCESS.2018.28822447(10691-10717)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2018.2882244
Kul GLuong DXie TChandola VKennedy OUpadhyaya S(2018)Similarity Metrics for SQL Query ClusteringIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.283121430:12(2408-2420)Online publication date: 1-Dec-2018
https://doi.org/10.1109/TKDE.2018.2831214
Show More Cited By

Index Terms

A Holistic Approach to OLAP Sessions Composition: The Falseto Experience
1. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques
    2. Software development process management

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Published In

cover image ACM Conferences

DOLAP '14: Proceedings of the 17th International Workshop on Data Warehousing and OLAP

November 2014

110 pages

ISBN:9781450309998

DOI:10.1145/2666158

General Chair:
Il-Yeol Song
Drexel University, USA
,
Program Chairs:
Alkis Simitsis
HP Labs, USA
,
Alfredo Cuzzocrea
ICAR-CNR and University of Calabria, Italy

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 November 2014

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November 7, 2014

Shanghai, China

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DOLAP '14 Paper Acceptance Rate 8 of 22 submissions, 36%;

Overall Acceptance Rate 29 of 79 submissions, 37%

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Cited By

Yousaf AKhattak AKhan K(2021)Ontology Evolution Using Recoverable SQL LogsService-Oriented Computing – ICSOC 2020 Workshops10.1007/978-3-030-76352-7_46(509-517)Online publication date: 30-May-2021
https://doi.org/10.1007/978-3-030-76352-7_46
Alvarez-Ayllon APalomo-Duarte MDodero J(2019)Interactive Data Exploration of Distributed Raw Files: A Systematic Mapping StudyIEEE Access10.1109/ACCESS.2018.28822447(10691-10717)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2018.2882244
Kul GLuong DXie TChandola VKennedy OUpadhyaya S(2018)Similarity Metrics for SQL Query ClusteringIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.283121430:12(2408-2420)Online publication date: 1-Dec-2018
https://doi.org/10.1109/TKDE.2018.2831214
Drushku KAligon JLabroche NMarcel PPeralta V(2018)Interest-based recommendations for business intelligence usersInformation Systems10.1016/j.is.2018.08.004Online publication date: Sep-2018
https://doi.org/10.1016/j.is.2018.08.004

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