Data Extraction and Exploration Tools for Business Intelligence

2019 ◽  
pp. 489-497
Author(s):  
Mário Cardoso ◽  
Tiago Guimarães ◽  
Carlos Filipe Portela ◽  
Manuel Filipe Santos
Keyword(s):  
Business Intelligence ◽  
Data Extraction

scholarly journals The Impact of Business Intelligence on Strategic Performance in Commercial Banks Operating in the Sate of Kuwait

2020 ◽  
Vol 13 (8) ◽  
pp. 91
Author(s):  
Hamad Salem Al-Merri
Keyword(s):  
Data Storage ◽  
Business Intelligence ◽  
Commercial Banks ◽  
Analytical Approach ◽  
Banking Sector ◽  
Data Extraction ◽  
Commercial Banking ◽  
Strategic Performance ◽  
The State Of Kuwait ◽  
The Impact

This study aimed to identify the impact of business intelligence on strategic performance in commercial banks operating in the State of Kuwait the researcher used the descriptive analytical approach to introduce both business intelligence and strategic performance. The study population consisted of employees working in top and middle management in commercial banks operating in State of Kuwait. Stratified random sample amounting 363 subjects was used. 270 questionnaires were collected representing 74.3% of the total sample. The study concluded that business intelligence system ensures data processing using data storage techniques and data extraction to obtain consistent and qualified information, thus providing the required knowledge to achieve the strategic goals and objectives by end users and executives in the future. The researcher recommends that Kuwaiti banks should keep pace with developments in the field of business intelligence to be employed in a better way in enhancing its strategic performance, in addition to conduct future studies that follow the analytical approach to deepen its utilization in Kuwaiti commercial banking sector.

scholarly journals State-of-the-art web data extraction systems for online business intelligence

2013 ◽  
Vol 64 ◽  
pp. 145-155
Author(s):  
Tomas Grigalis ◽  
Antanas Čenys
Keyword(s):  
Business Intelligence ◽  
State Of The Art ◽  
Data Extraction ◽  
Web Pages ◽  
Web Data ◽  
Web Data Extraction ◽  
Technological Advances ◽  
Online Business ◽  
A Company ◽  
Support Decision Making

The success of a company hinges on identifying and responding to competitive pressures. The main objective of online business intelligence is to collect valuable information from many Web sources to support decision making and thus gain competitive advantage. However, the online business intelligence presents non-trivial challenges to Web data extraction systems that must deal with technologically sophisticated modern Web pages where traditional manual programming approaches often fail. In this paper, we review commercially available state-of-the-art Web data extraction systems and their technological advances in the context of online business intelligence.Keywords: online business intelligence, Web data extraction, Web scrapingŠiuolaikinės iš tinklalapių duomenis renkančios ir verslo analitikai tinkamos sistemos (anglų k.)Tomas Grigalis, Antanas Čenys Santrauka Šiuolaikinės verslo organizacijos sėkmė priklauso nuo sugebėjimo atitinkamai reaguoti į nuolat besi­keičiančią konkurencinę aplinką. Internete veikian­čios verslo analitinės sistemos pagrindinis tikslas yra rinkti vertingą informaciją iš daugybės skirtingų internetinių šaltinių ir tokiu būdu padėti verslo orga­nizacijai priimti tinkamus sprendimus ir įgyti kon­kurencinį pranašumą. Tačiau informacijos rinkimas iš internetinių šaltinių yra sudėtinga problema, kai informaciją renkančios sistemos turi gerai veikti su itin technologiškai sudėtingais tinklalapiais. Šiame straipsnyje verslo analitikos kontekste apžvelgiamos pažangiausios internetinių duomenų rinkimo siste­mos. Taip pat pristatomi konkretūs scenarijai, kai duomenų rinkimo sistemos gali padėti verslo anali­tikai. Straipsnio pabaigoje autoriai aptaria pastarųjų metų technologinius pasiekimus, kurie turi potencia­lą tapti visiškai automatinėmis internetinių duomenų rinkimo sistemomis ir dar labiau patobulinti verslo analitiką bei gerokai sumažinti jos išlaidas.

scholarly journals Analysis of the NASH Efficiency Indicators in Brazilian Federal University Hospitals via Business Intelligence

2017 ◽  
Vol 3 (1) ◽  
pp. 89
Author(s):  
Carlo Alessandro Melo Noce ◽  
Georges Daniel Amvame Nze ◽  
Lourdes Mattos Brasil
Keyword(s):  
Information And Communication Technologies ◽  
Business Intelligence ◽  
Clinical Decision Making ◽  
Average Length ◽  
Data Extraction ◽  
Hospital Management ◽  
University Hospitals ◽  
National Agency ◽  
Major Step ◽  
Efficient Hospital

The hospital area is constantly in need of care and attention. Because of its urgencies, it has vulnerabilities and risks that hinder the quality of hospital management. Technological management tools are effective in improving processes and strategic administration because they provide information reliability. The aim of this work is to propose to the Brazilian’s Federal University Hospitals (BFUHs) and to the Brazilian Hospital Services Company (BHSC) the use of an open source Business Intelligence (BI) tool, Pentaho, to analyze the efficiency of Hospital Indicators (HIs) and to support the clinical decision-making. This paper describes BI and Pentaho, as well as the main points of the efficiency documentations established by the National Agency of Supplementary Health (NASH), with emphasis on the HIs: Hospital Occupancy Rates (HORs) and Averages Length of Stay (ALSs). The Pentaho does the data extraction and the transformation, as well as loading them into the Data Warehouse (DW), all based on a relational database from BHSC. After that, dimensional cubes are created for the generation of graphic panels in dashboards. Most BHSC hospitals are not yet adequately using their operational beds and neither managing correctly the average length of hospitals patients stay, being outside the goals established by NASH. Several steps are taken to achieve efficient hospital administration. However, the joint working of Information and Communication Technologies (ICTs) solutions with the health area and its standards provides a major step towards efficient hospital management.

Business Intelligence: Relationship between Capabilities, Success and Decision Environment

2014 ◽  
Vol 513-517 ◽  
pp. 4361-4365
Author(s):  
Sergey Kokin ◽  
Tie Nan Wang
Keyword(s):  
Data Analysis ◽  
Business Intelligence ◽  
Data Warehousing ◽  
Data Extraction ◽  
Theoretical Framework ◽  
Application Software ◽  
Lack Of Fit ◽  
Decision Environment ◽  
The Right ◽  
Tools And Techniques

The concept of Business Intelligence (BI) was first proposed in the late 1980-s. Since then the field of BI has experienced the rapid extension and development. More than 50 billion dollars have already been invested in different BI tools and application software, such as new desktop data analysis tools, data warehousing technologies, data extraction middleware and many other tools and techniques into the market. But not all the BI initiatives are successful. This paper posits that a key antecedent of BI success is having the right BI Capabilities, and right BI Capabilities depend on the Decision Environment in which the BI is used. Research suggests that a lack of fit between an organization and its BI is one of the reasons for lack of success. The match between the Decision Environment and what a BI provides has been studied as an indicator of success. The theoretical framework is proposed in this paper to study relationship between BI Capabilities, BI Success and Decision Environment

Exit-surface wave reconstruction using a focal series

1992 ◽  
Vol 50 (2) ◽  
pp. 988-989
Author(s):  
W.J. de Ruijter ◽  
M.R. McCartney ◽  
David J. Smith ◽  
J.K. Weiss
Keyword(s):  
Surface Wave ◽  
Spherical Aberration ◽  
Data Extraction ◽  
High Sensitivity ◽  
Geometric Distortion ◽  
Variation Method ◽  
Objective Lens ◽  
Immediate Reconstruction ◽  
Exit Surface ◽  
Electron Microscopes

Further advances in resolution enhancement of transmission electron microscopes can be expected from digital processing of image data recorded with slow-scan CCD cameras. Image recording with these new cameras is essential because of their high sensitivity, extreme linearity and negligible geometric distortion. Furthermore, digital image acquisition allows for on-line processing which yields virtually immediate reconstruction results. At present, the most promising techniques for exit-surface wave reconstruction are electron holography and the recently proposed focal variation method. The latter method is based on image processing applied to a series of images recorded at equally spaced defocus.Exit-surface wave reconstruction using the focal variation method as proposed by Van Dyck and Op de Beeck proceeds in two stages. First, the complex image wave is retrieved by data extraction from a parabola situated in three-dimensional Fourier space. Then the objective lens spherical aberration, astigmatism and defocus are corrected by simply dividing the image wave by the wave aberration function calculated with the appropriate objective lens aberration coefficients which yields the exit-surface wave.

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.

Od Business Intelligence do Business Performance Management

2012 ◽  
pp. 39-43
Author(s):  
Janusz Nesterak ◽  
Bernard Ziębicki
Keyword(s):  
Performance Management ◽  
Business Intelligence ◽  
Business Performance ◽  
Business Performance Management

Zarządzanie przedsiębiorstwem we współczesnych warunkach wymaga stosowania zaawansowanych systemów umożliwiających gromadzenie i przetwarzanie informacji do postaci użytecznej w podejmowaniu decyzji zarządczych. Możliwości takie stwarzają systemy klasy Business Intelligence. Systemy te obecnie są już szeroko stosowane w krajowych przedsiębiorstwach. Ostatnio coraz popularniejsze stają się systemy określane mianem Business Performance Management, które są traktowane jako kolejna generacja Business Intelligence. Istota systemów Business Performance Management dotychczas nie była szeroko prezentowane w literaturze krajowej. Część badaczy zajmujących się tą tematyką traktuje wymienione kategorie systemów jako tożsame. W artykule przedstawiono istotę systemów Business Performance Management oraz omówiono różnice pomiędzy tą kategorią rozwiązań i systemami Business Intelligence. Omówiono także elementy tworzące systemy Business Performance Management. Przedstawiono również metodykę oraz korzyści stosowania Business Performance Management w przedsiębiorstwach. (abstrakt oryginalny)

How Sweet and Ripe are the Fruits? Data Mining Techniques for Classifying and Predicting ‘Quick-Wins’ Direct Capital Investment in Indonesia as One Approach to Business intelligence Orientation and Knowledge Management Scenarios of Indonesian Enterprises

2019 ◽  
Vol 1 (1) ◽  
pp. 121-131
Author(s):  
Ali Fauzi
Keyword(s):  
Data Mining ◽  
Business Intelligence ◽  
Direct Investment ◽  
Capital Investment ◽  
Export Market ◽  
Added Value ◽  
Knowledge Generation ◽  
Management Scenarios ◽  
Data Mining Techniques ◽  
Knowledge Based Economy

The existence of big data of Indonesian FDI (foreign direct investment)/ CDI (capital direct investment) has not been exploited somehow to give further ideas and decision making basis. Example of data exploitation by data mining techniques are for clustering/labeling using K-Mean and classification/prediction using Naïve Bayesian of such DCI categories. One of DCI form is the ‘Quick-Wins’, a.k.a. ‘Low-Hanging-Fruits’ Direct Capital Investment (DCI), or named shortly as QWDI. Despite its mentioned unfavorable factors, i.e. exploitation of natural resources, low added-value creation, low skill-low wages employment, environmental impacts, etc., QWDI , to have great contribution for quick and high job creation, export market penetration and advancement of technology potential. By using some basic data mining techniques as complements to usual statistical/query analysis, or analysis by similar studies or researches, this study has been intended to enable government planners, starting-up companies or financial institutions for further CDI development. The idea of business intelligence orientation and knowledge generation scenarios is also one of precious basis. At its turn, Information and Communication Technology (ICT)’s enablement will have strategic role for Indonesian enterprises growth and as a fundamental for ‘knowledge based economy’ in Indonesia.

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