The Intentional Analytics Model (IAM) is a new paradigm to couple OLAP and analytics. It relies on two ideas: (i) letting the user explore data by expressing his/her analysis intentions rather than the data (s)he needs, and (ii) returning enhanced cubes, i.e., multidimensional data annotated with knowledge insights in the form of model components (e.g., clusters). In this paper we propose a proof-of-concept for the IAM vision by delivering an end-to-end implementation of describe, one of the five intention operators introduced by IAM.

Describing Multidimensional Data Through Highlights

Matteo Francia
;
Enrico Gallinucci;Matteo Golfarelli;Stefano Rizzi
2022

Abstract

The Intentional Analytics Model (IAM) is a new paradigm to couple OLAP and analytics. It relies on two ideas: (i) letting the user explore data by expressing his/her analysis intentions rather than the data (s)he needs, and (ii) returning enhanced cubes, i.e., multidimensional data annotated with knowledge insights in the form of model components (e.g., clusters). In this paper we propose a proof-of-concept for the IAM vision by delivering an end-to-end implementation of describe, one of the five intention operators introduced by IAM.
2022
SEBD 2022. Italian Symposium on Advanced Database Systems
36
43
Matteo Francia, Enrico Gallinucci, Matteo Golfarelli, Patrick Marcel, Veronika Peralta, Stefano Rizzi
File in questo prodotto:
File Dimensione Formato  
sebd22.pdf

accesso aperto

Tipo: Versione (PDF) editoriale
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione 1.51 MB
Formato Adobe PDF
1.51 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/893354
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact