Results 71 to 80 of about 34,455 (228)
大数据, 2015 OLAP (online analytical processing) is a key technology of business intelligence based on relational data. In big data era, people want to achieve high performance OLAP using a large cluster of ordinary nodes.
Xiaoyong Du, Yueguo Chen, Xiongpai Qin
doaj
Analyse multigraduelle OLAP [PDF]
Revue des nouvelles technologies - RNTI, E-15 (2009) 253-258, 2010 Decisional systems are based on multidimensional databases improving OLAP analyses. The paper describes a new OLAP operator named "BLEND" to perform multigradual analyses. The operation transforms multidimensional structures during querying in order to analyse measures according to various granularity levels, which are reorganised into a single ...
arxiv
XML Warehousing and OLAP [PDF]
Encyclopedia of Data Warehousing and Mining, Second Edition, IV,
IGI Publishing, pp.2109-2116, 2009, 2017 The aim of this article is to present an overview of the major XML warehousing approaches from the literature, as well as the existing approaches for performing OLAP analyses over XML data (which is termed XML-OLAP or XOLAP; Wang et al., 2005). We also discuss the issues and future trends in this area and illustrate this topic by presenting the design ...
arxiv
A Formal Algebra for OLAP [PDF]
arXiv, 2016 Online Analytical Processing (OLAP) comprises tools and algorithms that allow querying multidimensional databases. It is based on the multidimensional model, where data can be seen as a cube, where each cell contains one or more measures can be aggregated along dimensions.
arxiv
Collaborative OLAP with Tag Clouds: Web 2.0 OLAP Formalism and Experimental Evaluation
, 2016 Increasingly, business projects are ephemeral. New Business Intelligence tools must support ad-lib data sources and quick perusal. Meanwhile, tag clouds are a popular community-driven visualization technique.
Aouiche, Kamel +2 more
core +1 more source
Integrating E-Commerce and Data Mining: Architecture and Challenges [PDF]
, 2000 We show that the e-commerce domain can provide all the right ingredients for successful data mining and claim that it is a killer domain for data mining.
Ansari, Suhail +3 more
core +5 more sources
COOL: A framework for conversational OLAP
Information Systems, 2021 Matteo Francia +2 more
semanticscholar +1 more source
BUSINESS NEEDS FOR OLAP AND DATA MINING TOOLS: EVIDENCE FROM KOSOVO COMPANIES
Ekonomska Misao i Praksa, 2018 Background: This paper deals with topics relevant to problem of understanding how OLAP tools and DM applications integrate as well as how some information support systems can impact business processes of companies in Kosovo.
Aferdita Berisha Shaqiri +1 more
doaj
Olap aggregation function for textual data warehouse
International Conference on Enterprise Information Systems, 2016 For more than a decade, OLAP and multidimensional analysis have generated methodologies, tools and resource management systems for the analysis of numeric data.
F. Ravat, O. Teste, R. Tournier
semanticscholar +1 more source
Compacting Transactional Data in Hybrid OLTP & OLAP Databases [PDF]
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp.
1424-1435 (2012), 2012 Growing main memory sizes have facilitated database management systems that keep the entire database in main memory. The drastic performance improvements that came along with these in-memory systems have made it possible to reunite the two areas of online transaction processing (OLTP) and online analytical processing (OLAP): An emerging class of hybrid
arxiv