scholarly journals Business Intelligence – CDMB – Implementing BI-CMDB to Lower Operation Cost Expenses and Satisfy Increasing User Expectations

10.5772/16712 ◽  
2011 ◽  
Author(s):  
Vlad Nicolicin-Georgescu ◽  
Vincent Benatier ◽  
Remi Lehn ◽  
Henri Bri
Keyword(s):  
Business Intelligence ◽  
User Expectations ◽  
Operation Cost

A Systematic Review of User Expectations and Outcomes of Crisis Support Services

Crisis ◽  
2020 ◽  
pp. 1-9
Author(s):  
Kelly Mazzer ◽  
Megan O'Riordan ◽  
Alan Woodward ◽  
Debra Rickwood
Keyword(s):  
Systematic Review ◽  
Support Services ◽  
Text Message ◽  
Positive Outcomes ◽  
Online Chat ◽  
Online Databases ◽  
Personal Crisis ◽  
Crisis Support ◽  
User Expectations ◽  
Behavioural Sciences

Abstract. Background: Crisis support services play an important role in providing free, immediate access to support people in the community experiencing a personal crisis. Recently, services have expanded from telephone to digital modalities including online chat and text message services. This raises the question of what outcomes are being achieved for increasingly diverse service users across different modalities. Aims: This systematic review aimed to determine the expectations and outcomes of users of crisis support services across three modalities (telephone, online chat, and text message/SMS). Method: Online databases (CINAHL, MEDLINE, PsycARTICLES, PsycINFO, Psychological and Behavioural Sciences Collection) and gray literature were searched for studies measuring expectations and outcomes of crisis support services. Results: A total of 31 studies were included in the review, the majority of which were telephone-based. Similar expectations were found for telephone and online chat modalities, as well as consistently positive outcomes, measured by changes in emotional state, satisfaction, and referral plans. Limitations/Conclusion: There is a paucity of consistent outcome measures across and within modalities and limited research about users of text message/SMS services.

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.

Business Intelligence in der Gesetzlichen Krankenversicherung

Controlling ◽  
2010 ◽  
Vol 22 (12) ◽  
pp. 679-686
Author(s):  
Oliver Röniger
Keyword(s):  
Business Intelligence

Controlling für eine Industrie- und Handelskammer

Controlling ◽  
2019 ◽  
Vol 31 (4) ◽  
pp. 14-21
Author(s):  
Thomas Preuß ◽  
Dirk Nölken ◽  
Frank Kusterer
Keyword(s):  
Business Intelligence

Der CFO einer IHK wird zunehmend zum strategischen Partner der Führungskräfte sowie zum betriebswirtschaftlichen Dienstleister einer IHK-Organisation und deren Kunden. Ein Kunden- und Leistungs-Controlling auf Basis einer neuen Business-Intelligence Lösung bildet dabei ein wesentliches Instrument der Informationsversorgung.

Business Intelligence zur Unterstützung des Instandhaltungs- Controllings

Controlling ◽  
2006 ◽  
Vol 18 (1) ◽  
pp. 39-46
Author(s):  
Jörg Raimann ◽  
Lutz Mähler
Keyword(s):  
Business Intelligence

BI-gestütztes Controlling-Cockpit für den Unternehmensbereich IT

Controlling ◽  
2020 ◽  
Vol 32 (3) ◽  
pp. 80-85
Author(s):  
Alexander Growe ◽  
Marco Boehle ◽  
Dietmar Schön
Keyword(s):  
Business Intelligence ◽  
It Controlling

Aufgrund der sich verändernden Rolle der Unternehmens-IT hin zum Innovationstreiber kommt dem IT-Controlling eine zunehmend größere Bedeutung zu. Das hier vorgestellte Business-Intelligence-gestützte Controlling-Cockpit zeigt auf, wie durch eine auf die Anforderungen des Unternehmens abgestimmte Kennzahlenübersicht die Analyse und Steuerung des IT-Bereichs unterstützt werden kann.

Business Intelligence als Enabler des Basel II-Berichtswesens

Controlling ◽  
2009 ◽  
Vol 21 (10) ◽  
pp. 538-544 ◽  
Author(s):  
Roland Gabriel ◽  
Guido Golla ◽  
Tobias Hoppe ◽  
Alexander Pastwa ◽  
Pantcho Roussev
Keyword(s):  
Business Intelligence ◽  
Basel Ii
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