Specification-based data reduction in dimensional data warehouses

Skyt, Janne; Jensen, Christian S.; Pedersen, Torben Bach

doi:10.1016/j.is.2007.06.001

Cited by 18 publications

(23 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the multidimensional area, [11] presents a technique for progressive data aggregation of a fact. This study intends to specify data aggregation criteria of a fact due to higher levels of dimensions.…”

Section: Related Workmentioning

confidence: 99%

“…Hence a DW stores a huge volume of data in which the decision maker may well get lost during his analyses. On the other hand, the pertinence of MDW data decreases with age: while detailed information is generally considered important for recent data [11], it may be of lesser interest for older data. As data value decreases with time, we implement selective deletion at low levels of granularity according to the users' needs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reducing Multidimensional Data

Atigui

Ravat

Song

et al. 2014

Data Warehousing and Knowledge Discovery

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reducing Multidimensional Data

Atigui

Ravat

Song

et al. 2014

Data Warehousing and Knowledge Discovery

View full text Add to dashboard Cite

“…For example, data reduction in dimensional data warehouses can be achieved by aggregating data to higher levels in the dimensions, as described by Skyt et al [8].…”

Section: Related Workmentioning

confidence: 99%

Granularity reduction in temporal document databases

Nørvåg

2006

Information Systems

View full text Add to dashboard Cite

“…Although a number of isolated data integration [1] - [5], data aggregation [12] - [15] and data exchange techniques [16] - [18] have already been proposed. To the best of our knowledge the work presented in this paper is the first to design and implement an integrated, effective, easy to use and flexible solution for data integration, aggregation and exchange in the farming business.…”

Section: Introductionmentioning

confidence: 99%

Integration, aggregation and exchange of farming device data: A high level perspective

Iftikhar

2009

2009 Second International Conference on the Applications of Digital Information and Web Technologies

View full text Add to dashboard Cite

Most of the farming devices produce massive amounts of data. In most of the cases, it is necessary to store this data at a central location for further processing. Due to the huge volumes of data, strategies for data aggregation procedures are very important, in order to avoid oversized data sets. There is also an increasing need to share or exchange data with other stack holders in the farming business based on farming standards. This paper presents an integrated, effective, easy-to-use and flexible solution, which enables the farmers to integrate data from several farming devices, aggregate data at different granularity levels and exchange data bi-directionally with other farming systems. The paper also describes the implementation strategy based on a case study using farming standards and open source technologies.

show abstract

Specification-based data reduction in dimensional data warehouses

Cited by 18 publications

References 12 publications

Reducing Multidimensional Data

Reducing Multidimensional Data

Granularity reduction in temporal document databases

Integration, aggregation and exchange of farming device data: A high level perspective

Contact Info

Product

Resources

About