On relationships offering new drill-across possibilities

Abelló, Alberto; Samos, José; Saltor, Fèlix

doi:10.1145/583890.583892

Cited by 26 publications

(23 citation statements)

References 8 publications

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“…One Fact and several Dimensions to analyze it give raise to a Star. As already discussed in [1], we consider that it is important to be able to relate different Stars to facilitate the Drill-across operation. Thus, as we can see in figure 1, we could find two Facts (i.e.…”

Section: Figure 1: Example Of Multi-star Schemamentioning

confidence: 99%

“…In [1], we systematically showed how and which semantic relationships can be used to relate multidimensional constructs. Semantic relationships in the multidimensional schema define functions between Classes.…”

Section: New Drill-across Possibilitiesmentioning

confidence: 99%

“…The PK of each subclass would point to that of the superclass. We argued in [1] If Do is a superclass of D i , we will always be able to change the base of the space by adding the new table and linking it to its subclass. On the other hand, if D i is superclass of Do, we can only change the base if the specialization criterion of Do subsumes the condition of the WHERE clause of c i .…”

Section: Generalizationmentioning

confidence: 99%

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Implementing operations to navigate semantic star schemas

Abelló

Samos

Saltor

2003

Proceedings of the 6th ACM International Workshop on Data Warehousing and OLAP - DOLAP '03

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In the last years, lots of work have been devoted to multidimensional modeling, star shape schemas and OLAP operations. However, "drill-across" has not captured as much attention as other operations. This operation allows to change the subject of analysis keeping the same analysis space we were using to analyze another subject. It is assumed that this can be done if both subjects share exactly the same analysis dimensions. In this paper, besides the implementation of an algebraic set of operations on a RDBMS, we are going to show when and how we can change the subject of analysis in the presence of semantic relationships, even if the analysis dimensions do not exactly coincide.

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Section: Figure 1: Example Of Multi-star Schemamentioning

confidence: 99%

Section: New Drill-across Possibilitiesmentioning

confidence: 99%

Section: Generalizationmentioning

confidence: 99%

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Implementing operations to navigate semantic star schemas

Abelló

Samos

Saltor

2003

Proceedings of the 6th ACM International Workshop on Data Warehousing and OLAP - DOLAP '03

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“…Our notion of compatibility has been inspired by this work, but extends and formalizes Kimball's notion of conformity in a way that, we believe, is more suitable to autonomous data mart integration. Abellò et al [1] have investigated four kinds of relationships among dimensions and facts (derivation, generalization, association, and flow) that are relevant to drillacross navigation. Although our notion of compatibility is related to these kinds of relationships, the goals of the papers differ, since we refer to drill-across queries whereas [1] refers a weaker form of drill acrossing, specific to interactive navigation.…”

Section: Introductionmentioning

confidence: 99%

“…Abellò et al [1] have investigated four kinds of relationships among dimensions and facts (derivation, generalization, association, and flow) that are relevant to drillacross navigation. Although our notion of compatibility is related to these kinds of relationships, the goals of the papers differ, since we refer to drill-across queries whereas [1] refers a weaker form of drill acrossing, specific to interactive navigation. Some work has been done on the problem of integrating data marts with external data stored in various formats: object-oriented [13] and XML [12].…”

Section: Introductionmentioning

confidence: 99%

On the integration of autonomous data marts

Cabibbo¹,

Torlone²

Proceedings. 16th International Conference on Scientific and Statistical Database Management, 2004.

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Design and Development of a Tool for Integrating Heterogeneous Data Warehouses

Torlone

Panella

2005

Data Warehousing and Knowledge Discovery

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Abstract. In this paper we describe the design of a tool supporting the integration of independently developed data warehouses, a problem that arises in several common scenarios. The basic facility of the tool is a test of the validity of a matching between heterogeneous dimensions, according to a number of desirable properties. Two strategies are then provided to perform the actual integration. The first approach refers to a scenario of loosely coupled integration, in which we just need to identify the common information between sources and perform drill-across queries over them. The goal of the second approach is the derivation of a materialized view built by merging the sources, and refers to a scenario of tightly coupled integration in which queries are performed against the view. We illustrate architecture and functionality of the tool and the underlying techniques that implement the two integration strategies.

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On relationships offering new drill-across possibilities

Cited by 26 publications

References 8 publications

Implementing operations to navigate semantic star schemas

Implementing operations to navigate semantic star schemas

On the integration of autonomous data marts

Design and Development of a Tool for Integrating Heterogeneous Data Warehouses

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