Results 231 to 240 of about 24,203,637 (299)

Depth prediction of urban flood under different rainfall return periods based on deep learning and data warehouse.

Science of the Total Environment, 2020
With the global climate change and the rapid urbanization process, there is an increase in the risk of urban floods. Therefore, undertaking risk studies of urban floods, especially the depth prediction of urban flood is very important for urban flood ...
Zening Wu, Yihong Zhou, Huiliang Wang, Zi-hao Jiang   +3 more
semanticscholar   +1 more source

Data Warehouse Testing

International Journal of Data Warehousing and Mining, 2011
Testing is an essential part of the design life-cycle of a software product. Although most phases of data warehouse design have received considerable attention in the literature, not much research has been conducted concerning data warehouse testing. In this paper, the authors introduce a number of data mart-specific testing activities, classify them ...
GOLFARELLI, MATTEO, RIZZI, STEFANO
openaire   +1 more source

Designing and Implementing Data Warehouse for Agricultural Big Data

BigData Congress [Services Society], 2019
In recent years, precision agriculture that uses modern information and communication technologies is becoming very popular. Raw and semi-processed agricultural data are usually collected through various sources, such as: Internet of Thing (IoT), sensors,
V. M. Ngo, Nhien-An Le-Khac, Mohand Tahar Kechadi   +2 more
semanticscholar   +1 more source

Big Data Augmentation with Data Warehouse: A Survey

2018 IEEE International Conference on Big Data (Big Data), 2018
With dynamic changes in world’s technology, an increasing growth and adoption observed in the usage of social media, computer networks, internet of things, and cloud computing.
Umar Aftab, G. F. Siddiqui
semanticscholar   +1 more source

Data Warehouse Fixer: Fixing Inconsistencies in Data Warehouses

2011 30th International Conference of the Chilean Computer Science Society, 2011
Dimensions in Data Warehouses (DWs) are set of elements connected by a hierarchical relationship. Usually, dimensions are required to be strict and covering to support summarizations at different levels of granularity. A dimension is strict if all they rollup relations are functions, and is covering if every element in a category is connected with an ...
M. Caniupan, A. Placencia
openaire   +1 more source

Data warehouse architecture classification

2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2017
The purpose of this study is to give an overlook and comparison of best known data warehouse architectures. Single-layer, two- layer, and three-layer architectures are structure-oriented one that are depending on the number of layers used by the architecture.
Blažić, Gordana, Poščić, Patrizia, Jakšić, Danijela   +2 more
openaire   +2 more sources

Deductive Data Warehouses

2019
This chapter presents the concept of “deductive data warehouses.” Deductive data warehouses rely on deductive databases but use a data warehouse in the background instead of a database. The authors show how Datalog, as a logic programming language, can be used to perform on-line analytical processing (OLAP) analysis on data.
openaire   +1 more source

From Data Warehouse to Information Warehouse

Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, 2018
Data and information are different constructs and Data become information when they supply a content from several elements, generating thus a meaning. From this observation, in this paper, we introduce the paradigm of information warehousing and explain our motivation. We propose a generic and original information warehouse architecture for the storage
Hadjer Moulai, Habiba Drias
openaire   +1 more source

Data mining a diabetic data warehouse

Artificial Intelligence in Medicine, 2002
Diabetes is a major health problem in the United States. There is a long history of diabetic registries and databases with systematically collected patient information. We examine one such diabetic data warehouse, showing a method of applying data mining techniques, and some of the data issues, analysis problems, and results.
Joseph L, Breault, Colin R, Goodall, Peter J, Fos   +2 more
openaire   +2 more sources

Data Warehouse Systems: Design and Implementation

Data-Centric Systems and Applications, 2022
A. Vaisman, E. Zimányi
semanticscholar   +1 more source