Towards a proficient business intelligence for energy efficiency domain - prerequisites and data sources

被引:0
作者
Gawin, Bartlomiej [1 ]
Marcinkowski, Bartosz [1 ]
机构
[1] Univ Gdansk, Dept Business Informat, PL-80952 Gdansk, Poland
来源
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ICT MANAGEMENT FOR GLOBAL COMPETITIVENESS AND ECONOMIC GROWTH IN EMERGING ECONOMIES (ICTM 2016) | 2016年
关键词
Business Intelligence; BI; Energy Efficiency; Facility Management; NEURAL-NETWORKS;
D O I
暂无
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Business Intelligence (BI) has been introduced in different areas in order to take better decisions and it provides diverse levels of information to the stakeholders, based on their information needs. Some organizations apply BI to control their energy costs. To achieve comprehensive knowledge of all factors that affect energy consumption, BI systems in energy efficiency (EE) domain must be supplied with large amounts of data from different sources. The data are transformed into information and advanced analysis tools enable deep insight into energy consumption reasons and relationships with other factors. The knowledge gained this way improves management of the energy usage. Within this paper, authors perform a subject-related literature review on recent works of BI implementation in EE domain. Data sources for Business Intelligence analysis in the aforementioned domain are identified, enabling future in-depth research aimed at estimating dependencies and patterns regarding electricity consumption.
引用
收藏
页码:76 / 86
页数:11
相关论文
共 28 条
[1]  
Affeldt Fabrício Sobrosa, 2013, JISTEM J.Inf.Syst. Technol. Manag., V10, P251
[2]   A survey on recent research in business intelligence [J].
Aruldoss, Martin ;
Travis, Miranda Lakshmi ;
Venkatesan, V. Prasanna .
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT, 2014, 27 (06) :831-+
[3]   Business intelligence as a key strategy for development organizations [J].
Azma, Fereydoon ;
Mostafapour, Mohammad Ali .
FIRST WORLD CONFERENCE ON INNOVATION AND COMPUTER SCIENCES (INSODE 2011), 2012, 1 :102-106
[4]  
Bahrami M., 2012, Procedia - Social and Behavioral Sciences, V41, P160
[5]   A quantitative correlation coefficient mining method for business intelligence in small and medium enterprises of trading business [J].
Cheung, C. F. ;
Li, F. L. .
EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (07) :6279-6291
[6]   Understanding consumer heterogeneity: A business intelligence application of neural networks [J].
Hayashi, Yoichi ;
Hsieh, Ming-Huei ;
Setiono, Rudy .
KNOWLEDGE-BASED SYSTEMS, 2010, 23 (08) :856-863
[7]  
Hoss F., 2012, ELECT LIGHT POWER, V90, P40
[8]   Employing a recommendation expert system based on mental accounting and artificial neural networks into mining business intelligence for study abroad's P/S recommendations [J].
Hsieh, Kun-Lin .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (12) :14376-14381
[9]  
Inmon W. H., 2005, ''Building Data Warehouse
[10]  
International Facility Management Association, YEAR REV IFMA FY 201