Implementing Business Intelligence in Textile Industry

Size: px
Start display at page:

Download "Implementing Business Intelligence in Textile Industry"

Transcription

1 Implementing Business Intelligence in Textile Industry Are Managers Satisfied? 1 Kornelije Rabuzin, 2 Darko Škvorc, 3 Božidar Kliček 1,Kornelije Rabuzin University of Zagreb, Faculty of organization and informatics Varazdin, Croatia, 2 University of Zagreb, Faculty of organization and informatics Varazdin, Croatia, 3 University of Zagreb, Faculty of organization and informatics Varazdin, Croatia, Abstract In this paper we show how a business intelligence solution was implemented within the textile industry. Before the implementation phase took place, we explored whether different levels of management could use information technology and business intelligence in order to build reports on their own. As it turned out, they were all using computers on a daily basis and they said that they would use business intelligence in order to make better decisions. After the system was implemented, we built another questionnaire and we used another application to detect whether the system was useful and used. As it turned out, the system was well designed and useful, but managers didn t use the business intelligence system. In fact, they increased the number of requests and the IT department had to create even more reports than earlier. 1. Introduction Keywords: Data warehouse, Business intelligence (BI), Textile industry In the past decades many applications were built in order to support different business processes. As a consequence, one can find many examples, i.e., companies that have similar problems. Although many applications (information systems) exist (within some company), they are not compatible. When one has many systems to search for a piece of information, the process of finding that piece of information may be expensive and many steps may be required to get some result. Moreover, when one needs another piece of information, one has to do the things (steps) all over again and that is not something that one should encourage. Business intelligence and data warehouses became popular in the past decade (although they are a little bit older) because they tried to solve the problems that many incompatible applications and information systems imposed. When you build a central data structure called a data warehouse, many reports can be built within seconds and one can make decisions based on clean and integrated data coming from different sources. However it is not easy to build a data warehouse and many things can go wrong along the way. People that use data warehouses know what Extract-Transform-Load (ETL) is and they know how much time it takes and what problems it has to solve. Just to get an idea, some members of our team worked on a few such projects including a project that had to integrate sales data for two grocery stores from two different locations. In this particular project, both grocery stores used the same application, although that doesn t have to be the case. Before a data warehouse was built, it was not possible to compare the sales data from two stores at all. Namely, although products sold in those stores were the same, each store used different product id and different product name (for same products). As such, one couldn t just compare products by their name or id. In order to do so, data had to be cleaned and one common table of products had to be built. This new table was then connected to the sales data (sales data had to be moved to another table called a fact table, but we skip the details). So when building one such common table, you have to resolve different problems like missing data, wrong data, incomplete data, etc. More information regarding Data Warehouses (DW), ETL and Business Intelligence (BI) can be found in references [6], [9] and [12]. If one looks back, companies that had more capital and that were more profitable usually invested in BI solutions. Some industries that are not so profitable don t have enough money to invest is such International Journal of Information Processing and Management (IJIPM) Volume 6, Number 1, February

2 projects as such project can be expensive, especially in the beginning. Reasons as to why BI was not used/implement within the textile industry in Croatia have already been explored in a previous paper [15]. In that paper results were presented that we obtained by building a questionnaire for manager and IT professionals within the industry. Some interesting answers are used in this paper as well. As one can find in [15]: In recent years many articles were published on BI and different aspects of implementation of BI systems. Articles that can be found usually describe what we would call the best practice from the areas where business intelligence has been applied successfully, such as the telecommunication sector, financial sector, etc. ([2], [8], [14]). There are only a few studies that present implementations in other business areas like industry, tourism, etc. In most of those papers business intelligence is analyzed only from the perspective of IT professionals (specialists) and deals with technical aspects of implementation (methods of data mining and data warehousing, analytical tools for data processing, etc.). A small number of papers deals with issues related to organizational aspects of business intelligence implementation like project management, critical success factors, etc. [5]. In [7] authors show that theoretical research dominates among published articles. In [11] authors point out the insufficient number of papers that contain a comprehensive, empirically validated and generally applicable methodology and guideline for implementation of BI systems, although a few can be found. In [10] the authors propose a Business Intelligence Roadmap, in [17] a methodology that puts accent on high quality artificial intelligence tools is proposed, and in [18] the authors put accent on critical success factors to implement a BI system. Other interesting references are [1], [3] and [4] as well. When one builds a BI system, many problems are more likely to occur. According to SAS, the problems are [14]: - BI tools are too expensive, - there are no IT professionals in the field, - benefits of BI systems are not obvious and cannot be measured, - top management doesn t support such projects, - the organizational climate is not appropriate, etc. In [15] we tried to identify and explore why BI was not used in Croatian textile industry. As we wrote in [15]: In order to determine the current state of the art regarding the management decision-making process and to examine the reasons why BI is not used in the Croatian textile industry, the survey was conducted among managers and IT professionals employed in the Croatian textile industry. The main goals of this study were (for managers) to determine their opinion on the importance of information in decision-making process, to determine which sources of data and which software packages are used by managers in the decision-making processes, to determine their opinion on business intelligence, to examine their opinion on the reasons why BI is not implemented in their company and to determine the degree to which managers embrace new technologies. Regarding the IT specialists, we wanted to determine their opinion on BI and why BI has not yet been implemented in their company. The results that we got were attention-grabbing for sure. In this paper authors describe how a BI system was implemented and used, i.e., authors also measured the customer satisfaction. The paper is organized as follows; in the first part we present some questions and answers from the questionnaire and then we present the BI system that was developed. Then we describe (briefly) how the system was used (customer satisfaction) and in the end the conclusion is presented. 2. Questionnaire In [15] we used two questionnaires that were prepared according to the IBM guidelines which can be found in [13]. In [13] one can find questions that can be used to determine whether a company is a good candidate to implement the BI system. Since more profitable companies invest capital in BI solutions, some companies do know what BI is and are aware of its importance. However, they do not invest in such solutions. In order to determine why that is so, a survey was conducted within the Croatian textile industry which included managers as well as IT professionals. The results that we received from managers are listed in the table below (Table 1); first column contains the question and second column contains their answers (more information on the sample can be found in [15]): 2

3 Question Can you notice positive and negative trends in the business as well as opportunities and problems in your company and its environment? Does your company perform detailed market research before placing a new product to the market? Do you have accurate, complete and prompt information needed for decision making? Do you make decisions based on information from business reports or based on your experience and intuition? Regarding the previous question, the managers were also asked which activity was more time-consuming: report or decision-making. Do you know what Key Performance Indicators (KPI) are? Which data sources do you use when making decisions? Do you know what Business Intelligence is? Managers were then offered a brief explanation of the term "Business intelligence", and they were asked whether such a system was needed in their company or not. Do you think that your company is ready to implement the BI system i.e. does it fulfill all technical, human, financial and organizational requirements necessary for successful implementation? Table 1. Answers received from managers Answer (managers) - 68 % responded that they generally could notice trends - 20 % responded that they couldn t notice trends - 12 % responded that they could always notice opportunities and problems - 44 % answered that they did not have this kind of information - 32 % thought that the company did not perform market research - 24 % thought that the company performed market research only partially - 56 % said that they always had accurate and complete information - 36 % said that they mostly didn't have accurate and complete information - 60 % said that their decisions were mainly based on the information from business reports - 32 % said that they made decisions based on their own experience and intuition - 68 % responded that they spent more time on collecting data and preparing reports - 24 % said that they spent more time on decision-making - 8 % didn t know - 88 % responded that they knew what key performance indicators were - 12 % responded that they didn t know what key performance indicators were Furthermore: - 48 % monitored key performance indicators periodically - 32 % monitored key performance indicators regularly - 20 % didn't track key performance indicators at all % used internal sources, then data from the Internet (34.62 %) and then external data sources (25 %) - 52 % knew what BI was - 40 % heard about BI but they only partially knew what BI was - 8 % heard about BI, but they had no idea what it was - 84 % thought that such a system was required and should be implemented - 16 % believed that the BI system was needed, but the moment to implement such a system was not appropriate - 36 % thought that the company was not ready and that it would be ready in the near future - an equal number of managers believed that the company was not ready yet, but that it would be ready in the near future - 24 % were not able to answer that question - 4 % thought that the company was ready for implementation 3

4 Figure 1 shows the main reasons that managers indicated why the BI system was not yet implemented (each manager had to pick three possible reasons): Figure 1. What are the main reasons why BI is still not used in your company? In the end we used TRI index ([16]) to see whether managers would use new technologies, including business intelligence as well. As we already wrote in [15], TRI evaluates whether a person is a "technology type" (person accepts technology) or a "non-technology type" (person rejects technology). The methodology consists of several statements and for each statement respondents must choose whether they agree with it or not. The statements are related to various aspects of ICT, and they reflect a person's beliefs and opinions about ICT. Their answers are shown in the next figure: Figure 2. The opinion of managers about ICT (according to the TRI methodology) 4

5 We also built another questionnaire to see what IT people working in the company thought about BI solutions and managers in their company. Their answers can be summarized as follows (for more information one should look at [15]): - Most IT specialists (88.89 %), knew what business intelligence was; - Most IT specialists (88.89 %) believed that their company needed a BI system and that such system should be implemented; - Some IT specialists (55.56 %) had no experience with business intelligence development tools, and % had only some experience; - Regarding the implementation process, % considered that their company was not ready to implement such a system. It is interesting to see what IT specialists thought about main reasons why BI was not yet implemented (Figure 3): Figure 3. The main reasons why BI is not used in the company As one can see, many insights have been revealed. Furthermore, the company turned out to be a very good candidate for BI implementation, although people thought that the time to implement such a system was not right. 3. Data warehouse model Based on the results above, it was decided that a data warehouse should be implemented and several data marts were developed with only one external consultant (Figure 4): Figure 4. The developed data warehouse model 5

6 Database management system that was used in the company was Oracle. Because of that Oracle Warehouse Builder was used to build the data warehouse, and QlikView and RapidMiner tools were used for reporting and data analysis. Here we skip the technical details (the implementation phase was not too complex). After the system was implemented, different reports were built in a matter of seconds. We do not show them all for obvious reasons; one report just shows sales data (quantity) per regions (Figure 5): Figure 5. Sales data per region After the BI solution was implemented, we decided to test what people thought about it. Another even more important item that our team tested was customer satisfaction. The results are presented below. 4. Customer satisfaction After the implementation phase was over, users started to use the developed solution and we started to measure their satisfaction with the system. In order to do that, two things were done: - another questionnaire was built (for managers); - a small application was used to track requests for reports that were sent to the IT department. The first question in the questionnaire tested manager s satisfaction with the system. 78,26 % of them answered that they were very satisfied with the system and 21,74 % answered that they were satisfied. Then they were asked whether the BI system satisfied their needs. 69,57 % of them responded that the system satisfies their needs entirely, and 30,43 % of them answered that the system satisfies their needs (mostly). The next step was to determine whether the system was easy to use. According to the answers that were received, reporting was simple, OLAP analysis was more complex and data mining was considered to be the most complex for managers (Figure 6). As shall be presented, although reporting was considered to be simple, users didn t use this feature very much. 6

7 Figure 6. Customer satisfaction The application that was used to track requests for different kinds of reports showed that after the BI system was implemented, the number of requests increased. This means that managers had an opportunity to use the BI system to produce reports on their own, but that didn t happen. Instead, the number of requests increased, i.e., they sent requests to the IT department (somebody in the IT department should create reports for them). According to the IT department, although the solution that was developed was simple, managers just didn t want to tackle with the new tools as it all seemed to be too complicated for them. After the system was implemented, the application that was used to store data on requests showed that the number of requests increased by 20 %. 5. Conclusion This paper presents how to implement a BI system in a company that may seem to be a good candidate to implement such a system. Before the implementation took place, a survey was conducted to see what people thought about such a solution. Some informative observations were revealed in the survey and they are presented in the paper. After the survey was conducted, the BI system was implemented and it began to be used on a daily basis. Another questionnaire was built and a small application was used to test customer satisfaction. Although the system turned out to be simple and intuitive, at least for reporting purposes, the developed solution was not used as we expected it to be. 6. References [1] Anderson, J., Kotsiopulos, A., Enhanced Decision Making using Data Mining: Applications for Retailers, Journal of Textile and Apparel, Technology and Management, vol. 2, [2] Business Week, Getting Smart About BI: Best Practices Deliver Real Value, New York, The McGraw-Hill Companies Inc., [3] Danis, D., Proulx, M., Improving ROI and Success Rate of Your Business Intelligence Project, Pyxies Technologies, [4] Howson, C., Successful Business Intelligence Secrets to Making BI Killer App, McGraw Hill, [5] Hwang, M., Success Factors for Business Intelligence: Perceptions of Business Professionals, In Proceedings of the 19th Annual Conference of the Association of Chinese Management Educators, Mount Pleasant, Central Michigan University, [6] Inmon, W. H., Building the Data Warehouse, Indianapolis, Wiley Publishing, USA, [7] Jourdan, Z., Rainer, R. K., Marshall, T. E. Business intelligence: An analysis of the literature, Information Systems Management, vol. 25, pp , [8] Khan, A. et al., Drivers and Barriers to Business Intelligence Adoption: A Case of Pakistan, In European and Mediterranean Conference on Information Systems 2010, Abu Dhabi, pp. 1-23,

8 [9] Kimbal, R., Ross, M. The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, Indianapolis, Wiley Publishing, [10] Moss, T. L., Atre, S., Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications, Addison-Wesley Professional, Boston, [11] Olzak, C., Ziemba, E. Approach to Building and Implementing Business Intelligence Systems, Interdisciplinary Journal of Information, Knowledge, and Management, vol. 2, [12] Rabuzin K., Deductive data warehouses, International journal of data warehousing and mining, vol. 10, no. 1, [13] Reinschmidt, J., Francoise, A., Business Intelligence Certification Guide, San Jose, IBM Corporation, [14] SAS Institute, Business intelligence Maturity and the quest for better performance: Why most organizations aren t realizing the full potential of BI and what successful organizations do differently, SAS Institute, downloaded: [15] Škvorc, D., Rabuzin, K., Business Intelligence in Croatian Textile Industry, The Global Management & Information Technology Research Conference 2012, The Business Review, Cambridge, vol. 19, no. 2, New York, USA, pp , [16] Techno Ready Marketing, The Technology Readiness Index, downloaded: [17] Thieruf, R., Effective business intelligence systems, Quorum Books, Westport, [18] Yeoh, W., Koronios, A., Gao, J., Managing the Implementation of Business Intelligence Systems: A Critical Success Factors Framework, International Journal of Enterprise Information Systems, vol. 4,

Deductive Data Warehouses and Aggregate (Derived) Tables

Deductive Data Warehouses and Aggregate (Derived) Tables Deductive Data Warehouses and Aggregate (Derived) Tables Kornelije Rabuzin, Mirko Malekovic, Mirko Cubrilo Faculty of Organization and Informatics University of Zagreb Varazdin, Croatia {kornelije.rabuzin,

More information

Ezgi Dinçerden. Marmara University, Istanbul, Turkey

Ezgi Dinçerden. Marmara University, Istanbul, Turkey Economics World, Mar.-Apr. 2016, Vol. 4, No. 2, 60-65 doi: 10.17265/2328-7144/2016.02.002 D DAVID PUBLISHING The Effects of Business Intelligence on Strategic Management of Enterprises Ezgi Dinçerden Marmara

More information

SUCCESS FACTORS FOR BUSINESS INTELLIGENCE: PERCEPTIONS OF BUSINESS PROFESSIONALS

SUCCESS FACTORS FOR BUSINESS INTELLIGENCE: PERCEPTIONS OF BUSINESS PROFESSIONALS SUCCESS FACTORS FOR BUSINESS INTELLIGENCE: PERCEPTIONS OF BUSINESS PROFESSIONALS Mark I. Hwang, Business Information Systems Department, Central Michigan University Mount Pleasant, MI 48859, (989) 774-5900,

More information

An Introduction to Data Warehousing. An organization manages information in two dominant forms: operational systems of

An Introduction to Data Warehousing. An organization manages information in two dominant forms: operational systems of An Introduction to Data Warehousing An organization manages information in two dominant forms: operational systems of record and data warehouses. Operational systems are designed to support online transaction

More information

BUSINESS INTELLIGENCE TOOLS FOR IMPROVE SALES AND PROFITABILITY

BUSINESS INTELLIGENCE TOOLS FOR IMPROVE SALES AND PROFITABILITY Revista Tinerilor Economişti (The Young Economists Journal) BUSINESS INTELLIGENCE TOOLS FOR IMPROVE SALES AND PROFITABILITY Assoc. Prof Luminiţa Şerbănescu Ph. D University of Piteşti Faculty of Economics,

More information

Methodology Framework for Analysis and Design of Business Intelligence Systems

Methodology Framework for Analysis and Design of Business Intelligence Systems Applied Mathematical Sciences, Vol. 7, 2013, no. 31, 1523-1528 HIKARI Ltd, www.m-hikari.com Methodology Framework for Analysis and Design of Business Intelligence Systems Martin Závodný Department of Information

More information

Data Mining Solutions for the Business Environment

Data Mining Solutions for the Business Environment Database Systems Journal vol. IV, no. 4/2013 21 Data Mining Solutions for the Business Environment Ruxandra PETRE University of Economic Studies, Bucharest, Romania ruxandra_stefania.petre@yahoo.com Over

More information

SUCCESSFUL IMPLEMENTATION OF BUSINESS INTELLIGENCE AS A TOOL FOR COMPANY MANAGEMENT Tomáš Mandičák, Peter Mesároš, Karol Hrubý. INTRODUCTION Nowadays, situation on the markets is not easy for companies.

More information

IMPROVING THE QUALITY OF THE DECISION MAKING BY USING BUSINESS INTELLIGENCE SOLUTIONS

IMPROVING THE QUALITY OF THE DECISION MAKING BY USING BUSINESS INTELLIGENCE SOLUTIONS IMPROVING THE QUALITY OF THE DECISION MAKING BY USING BUSINESS INTELLIGENCE SOLUTIONS Maria Dan Ştefan Academy of Economic Studies, Faculty of Accounting and Management Information Systems, Uverturii Street,

More information

Enterprise Solutions. Data Warehouse & Business Intelligence Chapter-8

Enterprise Solutions. Data Warehouse & Business Intelligence Chapter-8 Enterprise Solutions Data Warehouse & Business Intelligence Chapter-8 Learning Objectives Concepts of Data Warehouse Business Intelligence, Analytics & Big Data Tools for DWH & BI Concepts of Data Warehouse

More information

Data Warehousing: A Technology Review and Update Vernon Hoffner, Ph.D., CCP EntreSoft Resouces, Inc.

Data Warehousing: A Technology Review and Update Vernon Hoffner, Ph.D., CCP EntreSoft Resouces, Inc. Warehousing: A Technology Review and Update Vernon Hoffner, Ph.D., CCP EntreSoft Resouces, Inc. Introduction Abstract warehousing has been around for over a decade. Therefore, when you read the articles

More information

A review of business intelligence and its maturity models

A review of business intelligence and its maturity models African Journal of Business Management Vol. 5(9), pp. 3424-3428, 4 May, 2011 Available online at http://www.academicjournals.org/ajbm DOI: 10.5897/AJBM10.1564 ISSN 1993-8233 2011 Academic Journals Review

More information

The role of business intelligence in knowledge sharing: a Case Study at Al-Hikma Pharmaceutical Manufacturing Company

The role of business intelligence in knowledge sharing: a Case Study at Al-Hikma Pharmaceutical Manufacturing Company The role of business intelligence in knowledge sharing: a Case Study at Al-Hikma Pharmaceutical Manufacturing Company Samer Barakat 1* Hasan Ali Al-Zu bi 2 Hanadi Al-Zegaier 3 1. Management Information

More information

Republic Polytechnic School of Information and Communications Technology C355 Business Intelligence. Module Curriculum

Republic Polytechnic School of Information and Communications Technology C355 Business Intelligence. Module Curriculum Republic Polytechnic School of Information and Communications Technology C355 Business Intelligence Module Curriculum This document addresses the content related abilities, with reference to the module.

More information

INTELLIGENT RISK MANAGEMENT - A NEW PRINCIPLE IN RISK MANAGEMENT BASED ON USING BI IN RM

INTELLIGENT RISK MANAGEMENT - A NEW PRINCIPLE IN RISK MANAGEMENT BASED ON USING BI IN RM INTELLIGENT RISK MANAGEMENT - A NEW PRINCIPLE IN RISK MANAGEMENT BASED ON USING BI IN RM Valentin Petru Măzăreanu 1 Abstract The need for a system able to store information about the risks faced by the

More information

KEY FACTORS AND BARRIERS OF BUSINESS INTELLIGENCE IMPLEMENTATION

KEY FACTORS AND BARRIERS OF BUSINESS INTELLIGENCE IMPLEMENTATION KEY FACTORS AND BARRIERS OF BUSINESS INTELLIGENCE IMPLEMENTATION Peter Mesároš, Štefan Čarnický & Tomáš Mandičák The business environment is constantly changing and becoming more complex and difficult.

More information

Presented by: Jose Chinchilla, MCITP

Presented by: Jose Chinchilla, MCITP Presented by: Jose Chinchilla, MCITP Jose Chinchilla MCITP: Database Administrator, SQL Server 2008 MCITP: Business Intelligence SQL Server 2008 Customers & Partners Current Positions: President, Agile

More information

Utilizing IT in Government: Strategic View to Digital Dashboards

Utilizing IT in Government: Strategic View to Digital Dashboards 2011 3rd International Conference on Information and Financial Engineering IPEDR vol.12 (2011) (2011) IACSIT Press, Singapore Utilizing IT in Government: Strategic View to Digital Dashboards Nastaran Aliy

More information

Data Warehouse Architecture Overview

Data Warehouse Architecture Overview Data Warehousing 01 Data Warehouse Architecture Overview DW 2014/2015 Notice! Author " João Moura Pires (jmp@di.fct.unl.pt)! This material can be freely used for personal or academic purposes without any

More information

BENEFITS AND ADVANTAGES OF BUSINESS INTELLIGENCE IN CORPORATE MANAGEMENT

BENEFITS AND ADVANTAGES OF BUSINESS INTELLIGENCE IN CORPORATE MANAGEMENT International Journal of Latest Research In Engineering and Computing (IJLREC) Volume 3, Issue 1, Page No. 1-7 January-February 2015 www.ijlrec.com ISSN: 2347-6540 BENEFITS AND ADVANTAGES OF BUSINESS INTELLIGENCE

More information

Creating a Business Intelligence Competency Center to Accelerate Healthcare Performance Improvement

Creating a Business Intelligence Competency Center to Accelerate Healthcare Performance Improvement Creating a Business Intelligence Competency Center to Accelerate Healthcare Performance Improvement Bruce Eckert, National Practice Director, Advisory Group Ramesh Sakiri, Executive Consultant, Healthcare

More information

IMPROVING DATA INTEGRATION FOR DATA WAREHOUSE: A DATA MINING APPROACH

IMPROVING DATA INTEGRATION FOR DATA WAREHOUSE: A DATA MINING APPROACH IMPROVING DATA INTEGRATION FOR DATA WAREHOUSE: A DATA MINING APPROACH Kalinka Mihaylova Kaloyanova St. Kliment Ohridski University of Sofia, Faculty of Mathematics and Informatics Sofia 1164, Bulgaria

More information

BUSINESS INTELLIGENCE AND DATA WAREHOUSING. Y o u r B u s i n e s s A c c e l e r a t o r

BUSINESS INTELLIGENCE AND DATA WAREHOUSING. Y o u r B u s i n e s s A c c e l e r a t o r BUSINESS INTELLIGENCE AND DATA WAREHOUSING. Y o u r B u s i n e s s A c c e l e r a t o r About AccelTeam Leading intelligence solutions provider led by highly qualified professionals Industry vertical

More information

A Framework Correlating Decision Making Style and Business Intelligence Aspect

A Framework Correlating Decision Making Style and Business Intelligence Aspect 2012 3rd International Conference on e-education, e-business, e-management and e-learning IPEDR vol.27 (2012) (2012) IACSIT Press, Singapore A Framework Correlating Decision Making Style and Business Intelligence

More information

GRADUATE ENTREPRENEUR ANALYTICAL REPORTS (GEAR) USING DATA WAREHOUSE MODEL: A CASE STUDY AT CEDI, UNIVERSITI UTARA MALAYSIA (UUM).

GRADUATE ENTREPRENEUR ANALYTICAL REPORTS (GEAR) USING DATA WAREHOUSE MODEL: A CASE STUDY AT CEDI, UNIVERSITI UTARA MALAYSIA (UUM). GRADUATE ENTREPRENEUR ANALYTICAL REPORTS (GEAR) USING DATA WAREHOUSE MODEL: A CASE STUDY AT CEDI, UNIVERSITI UTARA MALAYSIA (UUM). Muhamad Shahbani Abu Bakar 1 and Hayder Naser Khraibet. 1 INTRODUCTION

More information

www.ijreat.org Published by: PIONEER RESEARCH & DEVELOPMENT GROUP (www.prdg.org) 28

www.ijreat.org Published by: PIONEER RESEARCH & DEVELOPMENT GROUP (www.prdg.org) 28 Data Warehousing - Essential Element To Support Decision- Making Process In Industries Ashima Bhasin 1, Mr Manoj Kumar 2 1 Computer Science Engineering Department, 2 Associate Professor, CSE Abstract SGT

More information

Outline Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications

Outline Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications Outline Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications Introduction to the BI Roadmap Business Intelligence Framework DW role in BI From Chaos to Architecture

More information

Faun dehenry FMT Systems Inc. faun.dehenry@fmtsystems.com. 2001-9, FMT Systems Inc. All rights reserved.

Faun dehenry FMT Systems Inc. faun.dehenry@fmtsystems.com. 2001-9, FMT Systems Inc. All rights reserved. Assessing BI Readiness Faun dehenry FMT Systems Inc. faun.dehenry@fmtsystems.com Agenda Introduction What is BI Organizational considerations Successful implementations BI assessment defined and assessment

More information

Assessment of Business Intelligence Maturity in the Selected Organizations

Assessment of Business Intelligence Maturity in the Selected Organizations Proceedings of the 2013 Federated Conference on Computer Science and Information Systems pp. 951 958 Assessment of Business Intelligence Maturity in the Selected Organizations Celina M. Olszak University

More information

Model Analysis of Data Integration of Enterprises and E-Commerce Based on ODS

Model Analysis of Data Integration of Enterprises and E-Commerce Based on ODS Model Analysis of Data Integration of Enterprises and E-Commerce Based on ODS Zhigang Li, Yan Huang and Shifeng Wan College of Information Management, Chengdu University of Technology, Chengdu 610059,

More information

The Current Business Intelligence Practice in Hong Kong

The Current Business Intelligence Practice in Hong Kong The Current Business Intelligence Practice in Hong Kong By Dr. Raymond Y.K. Lau and Johnny C.F. So Department of Information Systems, City University of Hong Kong And Hong Kong Computer Society Business

More information

INTELLIGENT PROFILE ANALYSIS GRADUATE ENTREPRENEUR (ipage) SYSTEM USING BUSINESS INTELLIGENCE TECHNOLOGY

INTELLIGENT PROFILE ANALYSIS GRADUATE ENTREPRENEUR (ipage) SYSTEM USING BUSINESS INTELLIGENCE TECHNOLOGY INTELLIGENT PROFILE ANALYSIS GRADUATE ENTREPRENEUR (ipage) SYSTEM USING BUSINESS INTELLIGENCE TECHNOLOGY Muhamad Shahbani, Azman Ta a, Mohd Azlan, and Norshuhada Shiratuddin INTRODUCTION Universiti Utara

More information

IS YOUR DATA WAREHOUSE SUCCESSFUL? Developing a Data Warehouse Process that responds to the needs of the Enterprise.

IS YOUR DATA WAREHOUSE SUCCESSFUL? Developing a Data Warehouse Process that responds to the needs of the Enterprise. IS YOUR DATA WAREHOUSE SUCCESSFUL? Developing a Data Warehouse Process that responds to the needs of the Enterprise. Peter R. Welbrock Smith-Hanley Consulting Group Philadelphia, PA ABSTRACT Developing

More information

Bussiness Intelligence and Data Warehouse. Tomas Bartos CIS 764, Kansas State University

Bussiness Intelligence and Data Warehouse. Tomas Bartos CIS 764, Kansas State University Bussiness Intelligence and Data Warehouse Schedule Bussiness Intelligence (BI) BI tools Oracle vs. Microsoft Data warehouse History Tools Oracle vs. Others Discussion Business Intelligence (BI) Products

More information

Presented By: Leah R. Smith, PMP. Ju ly, 2 011

Presented By: Leah R. Smith, PMP. Ju ly, 2 011 Presented By: Leah R. Smith, PMP Ju ly, 2 011 Business Intelligence is commonly defined as "the process of analyzing large amounts of corporate data, usually stored in large scale databases (such as a

More information

Research on Airport Data Warehouse Architecture

Research on Airport Data Warehouse Architecture Research on Airport Warehouse Architecture WANG Jian-bo FAN Chong-jun Business School University of Shanghai for Science and Technology Shanghai 200093, P. R. China. Abstract Domestic airports are accelerating

More information

How Effectively Are Companies Using Business Analytics? DecisionPath Consulting Research October 2010

How Effectively Are Companies Using Business Analytics? DecisionPath Consulting Research October 2010 How Effectively Are Companies Using Business Analytics? DecisionPath Consulting Research October 2010 Thought-Leading Consultants in: Business Analytics Business Performance Management Business Intelligence

More information

KNOWLEDGE BASE DATA MINING FOR BUSINESS INTELLIGENCE

KNOWLEDGE BASE DATA MINING FOR BUSINESS INTELLIGENCE KNOWLEDGE BASE DATA MINING FOR BUSINESS INTELLIGENCE Dr. Ruchira Bhargava 1 and Yogesh Kumar Jakhar 2 1 Associate Professor, Department of Computer Science, Shri JagdishPrasad Jhabarmal Tibrewala University,

More information

Data Warehousing and Data Mining

Data Warehousing and Data Mining Data Warehousing and Data Mining Part I: Data Warehousing Gao Cong gaocong@cs.aau.dk Slides adapted from Man Lung Yiu and Torben Bach Pedersen Course Structure Business intelligence: Extract knowledge

More information

BI Market Dynamics and Future Directions

BI Market Dynamics and Future Directions Inaugural Keynote Address Business Intelligence Conference Nov 19, 2011, New Delhi BI Market Dynamics and Future Directions Shashikant Brahmankar Head Business Intelligence & Analytics, HCL Content Evolution

More information

TOWARD A GREATER UNDERSTANDING OF BUSINESS INTELLIGENCE: SURVEY RESULTS

TOWARD A GREATER UNDERSTANDING OF BUSINESS INTELLIGENCE: SURVEY RESULTS TOWARD A GREATER UNDERSTANDING OF BUSINESS INTELLIGENCE: SURVEY RESULTS Mark I. Hwang, Business Information Systems Department, Central Michigan University Mount Pleasant, MI 48859, (989) 774-5900, mark.hwang@cmich.edu

More information

Course Design Document. IS417: Data Warehousing and Business Analytics

Course Design Document. IS417: Data Warehousing and Business Analytics Course Design Document IS417: Data Warehousing and Business Analytics Version 2.1 20 June 2009 IS417 Data Warehousing and Business Analytics Page 1 Table of Contents 1. Versions History... 3 2. Overview

More information

Business Process Management Systems and Business Intelligence Systems as support of Knowledge Management

Business Process Management Systems and Business Intelligence Systems as support of Knowledge Management Business Process Management Systems and Business Intelligence Systems as support of Knowledge Management Katarina Curko,Vesna Bosilj Vuksic Department of Business Computing Faculty of Economics & Business,

More information

The Impact Of Organization Changes On Business Intelligence Projects

The Impact Of Organization Changes On Business Intelligence Projects Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization, Beijing, China, September 15-17, 2007 414 The Impact Of Organization Changes On Business Intelligence Projects

More information

Introduction to Business Intelligence

Introduction to Business Intelligence IBM Software Group Introduction to Business Intelligence Vince Leat ASEAN SW Group 2007 IBM Corporation Discussion IBM Software Group What is Business Intelligence BI Vision Evolution Business Intelligence

More information

Survey of use of Data Warehousing and Business Intelligence at Australasian Universities 2008

Survey of use of Data Warehousing and Business Intelligence at Australasian Universities 2008 Data Warehousing Survey results (Jan ) Australasian Association for Institutional Research (AAIR) Data Warehouse Special Interest Group (SIG) Survey of use of Data Warehousing and Business Intelligence

More information

Data Warehousing Dashboards & Data Mining. Empowering Extraordinary Patient Care

Data Warehousing Dashboards & Data Mining. Empowering Extraordinary Patient Care Data Warehousing Dashboards & Data Mining Empowering Extraordinary Patient Care Your phone has been automatically muted. Please use the Q&A panel to ask questions during the presentation. Introduction

More information

Business Intelligence maturity model in organization on the base of the capability maturing model (CMM)

Business Intelligence maturity model in organization on the base of the capability maturing model (CMM) The Journal of Mathematics and Computer Science Available online at http://www.tjmcs.com The Journal of Mathematics and Computer Science Vol. 4 No.2 (2012) 110-119 Business Intelligence maturity model

More information

STRATEGIC AND FINANCIAL PERFORMANCE USING BUSINESS INTELLIGENCE SOLUTIONS

STRATEGIC AND FINANCIAL PERFORMANCE USING BUSINESS INTELLIGENCE SOLUTIONS STRATEGIC AND FINANCIAL PERFORMANCE USING BUSINESS INTELLIGENCE SOLUTIONS Boldeanu Dana Maria Academia de Studii Economice Bucure ti, Facultatea Contabilitate i Informatic de Gestiune, Pia a Roman nr.

More information

THE INTELLIGENT BUSINESS INTELLIGENCE SOLUTIONS

THE INTELLIGENT BUSINESS INTELLIGENCE SOLUTIONS THE INTELLIGENT BUSINESS INTELLIGENCE SOLUTIONS ADRIAN COJOCARIU, CRISTINA OFELIA STANCIU TIBISCUS UNIVERSITY OF TIMIŞOARA, FACULTY OF ECONOMIC SCIENCE, DALIEI STR, 1/A, TIMIŞOARA, 300558, ROMANIA ofelia.stanciu@gmail.com,

More information

The Business Value of Predictive Analytics

The Business Value of Predictive Analytics The Business Value of Predictive Analytics Alys Woodward Program Manager, European Business Analytics, Collaboration and Social Solutions, IDC London, UK 15 November 2011 Copyright IDC. Reproduction is

More information

BIG DATA. Value 8/14/2014 WHAT IS BIG DATA? THE 5 V'S OF BIG DATA WHAT IS BIG DATA?

BIG DATA. Value 8/14/2014 WHAT IS BIG DATA? THE 5 V'S OF BIG DATA WHAT IS BIG DATA? WHAT IS BIG DATA? BIG DATA DR. KLARA NELSON THE UNIVERSITY OF TAMPA "Volumes of data that are unusually large, or types of data that are unstructured" Thomas Davenport, Keeping Up with the Quants, 2013,

More information

The 7 th Balkan Conference on Operational Research BACOR 05 Constanta, May 2005, Romania DATA WAREHOUSE MANAGEMENT SYSTEM A CASE STUDY

The 7 th Balkan Conference on Operational Research BACOR 05 Constanta, May 2005, Romania DATA WAREHOUSE MANAGEMENT SYSTEM A CASE STUDY The 7 th Balkan Conference on Operational Research BACOR 05 Constanta, May 2005, Romania DATA WAREHOUSE MANAGEMENT SYSTEM A CASE STUDY DARKO KRULJ Trizon Group, Belgrade, Serbia and Montenegro. MILUTIN

More information

Master Data Management. Zahra Mansoori

Master Data Management. Zahra Mansoori Master Data Management Zahra Mansoori 1 1. Preference 2 A critical question arises How do you get from a thousand points of data entry to a single view of the business? We are going to answer this question

More information

A Knowledge Management Framework Using Business Intelligence Solutions

A Knowledge Management Framework Using Business Intelligence Solutions www.ijcsi.org 102 A Knowledge Management Framework Using Business Intelligence Solutions Marwa Gadu 1 and Prof. Dr. Nashaat El-Khameesy 2 1 Computer and Information Systems Department, Sadat Academy For

More information

BUILDING OLAP TOOLS OVER LARGE DATABASES

BUILDING OLAP TOOLS OVER LARGE DATABASES BUILDING OLAP TOOLS OVER LARGE DATABASES Rui Oliveira, Jorge Bernardino ISEC Instituto Superior de Engenharia de Coimbra, Polytechnic Institute of Coimbra Quinta da Nora, Rua Pedro Nunes, P-3030-199 Coimbra,

More information

LUCRĂRI ŞTIINŢIFICE, SERIA I, VOL. XII (2) BUSINESS INTELLIGENCE TOOLS AND THE CONCEPTUAL ARCHITECTURE

LUCRĂRI ŞTIINŢIFICE, SERIA I, VOL. XII (2) BUSINESS INTELLIGENCE TOOLS AND THE CONCEPTUAL ARCHITECTURE LUCRĂRI ŞTIINŢIFICE, SERIA I, VOL. XII (2) BUSINESS INTELLIGENCE TOOLS AND THE CONCEPTUAL ARCHITECTURE ARHITECTURA CONCEPTUALĂ ŞI INSTRUMENTE DE BUSINESS INTELLIGENTE LUMINIŢA ŞERBĂNESCU 1 1 University

More information

A Survey on Data Warehouse Architecture

A Survey on Data Warehouse Architecture A Survey on Data Warehouse Architecture Rajiv Senapati 1, D.Anil Kumar 2 1 Assistant Professor, Department of IT, G.I.E.T, Gunupur, India 2 Associate Professor, Department of CSE, G.I.E.T, Gunupur, India

More information

Challenges in developing a cost-effective data warehouse for a tertiary institution in a developing country

Challenges in developing a cost-effective data warehouse for a tertiary institution in a developing country Data Mining VII: Data, Text and Web Mining and their Business Applications 389 Challenges in developing a cost-effective data warehouse for a tertiary institution in a developing country A. Nazir & T.

More information

If you re serious about Business Intelligence, you need a BI Competency Centre

If you re serious about Business Intelligence, you need a BI Competency Centre If you re serious about Business Intelligence, you need a BI Competency Centre Michael Gibson Data Warehouse Manager Deakin University > > > > > > > > > The traditional Project Implementation model Project

More information

Deriving Business Intelligence from Unstructured Data

Deriving Business Intelligence from Unstructured Data International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 9 (2013), pp. 971-976 International Research Publications House http://www. irphouse.com /ijict.htm Deriving

More information

THE QUALITY OF DATA AND METADATA IN A DATAWAREHOUSE

THE QUALITY OF DATA AND METADATA IN A DATAWAREHOUSE THE QUALITY OF DATA AND METADATA IN A DATAWAREHOUSE Carmen Răduţ 1 Summary: Data quality is an important concept for the economic applications used in the process of analysis. Databases were revolutionized

More information

Master Data Management and Data Warehousing. Zahra Mansoori

Master Data Management and Data Warehousing. Zahra Mansoori Master Data Management and Data Warehousing Zahra Mansoori 1 1. Preference 2 IT landscape growth IT landscapes have grown into complex arrays of different systems, applications, and technologies over the

More information

DATA QUALITY IN BUSINESS INTELLIGENCE APPLICATIONS

DATA QUALITY IN BUSINESS INTELLIGENCE APPLICATIONS DATA QUALITY IN BUSINESS INTELLIGENCE APPLICATIONS Gorgan Vasile Academy of Economic Studies Bucharest, Faculty of Accounting and Management Information Systems, Academia de Studii Economice, Catedra de

More information

Achieving Rapid Return On Data Warehouse Investments

Achieving Rapid Return On Data Warehouse Investments Achieving Rapid Return On Data Warehouse Investments 1. Introduction Data warehouses are at the heart of most business intelligence solution platforms or frameworks and are expected to remain the foundation

More information

DESIGNING THE ANALYSIS REPORTS BY MEANS OF THE BI INSTRUMENTS

DESIGNING THE ANALYSIS REPORTS BY MEANS OF THE BI INSTRUMENTS DESIGNING THE ANALYSIS REPORTS BY MEANS OF THE BI INSTRUMENTS Luminiţa ŞERBĂNESCU UNIVERSITY OF PITEŞTI Abstract: A business intelligence process offers to the management an overall picture over the situation

More information

CUSTOMER RELATIONSHIP MANAGEMENT IN THE KINGDOM OF BAHRAIN Dr. Adel I. Al-Alawi, University of Bahrain, alalawi@itc.uob.bh

CUSTOMER RELATIONSHIP MANAGEMENT IN THE KINGDOM OF BAHRAIN Dr. Adel I. Al-Alawi, University of Bahrain, alalawi@itc.uob.bh CUSTOMER RELATIONSHIP MANAGEMENT IN THE KINGDOM OF BAHRAIN Dr. Adel I. Al-Alawi, University of Bahrain, alalawi@itc.uob.bh ABSTRACT Customer Relationship Management (CRM) is a new weapon to satisfy customers

More information

Dimensional Modeling for Data Warehouse

Dimensional Modeling for Data Warehouse Modeling for Data Warehouse Umashanker Sharma, Anjana Gosain GGS, Indraprastha University, Delhi Abstract Many surveys indicate that a significant percentage of DWs fail to meet business objectives or

More information

DECISION SUPPORT SYSTEMS IN INFORMATION TECHNOLOGY ASSIMILATION

DECISION SUPPORT SYSTEMS IN INFORMATION TECHNOLOGY ASSIMILATION DECISION SUPPORT SYSTEMS IN INFORMATION TECHNOLOGY ASSIMILATION Roger L. Hayen, Central Michigan University, roger.hayen@cmich.edu Monica C. Holmes, Central Michigan University, monica.holmes@cmich.edu

More information

HELSINKI UNIVERSITY OF TECHNOLOGY 26.1.2005 T-86.141 Enterprise Systems Integration, 2001. Data warehousing and Data mining: an Introduction

HELSINKI UNIVERSITY OF TECHNOLOGY 26.1.2005 T-86.141 Enterprise Systems Integration, 2001. Data warehousing and Data mining: an Introduction HELSINKI UNIVERSITY OF TECHNOLOGY 26.1.2005 T-86.141 Enterprise Systems Integration, 2001. Data warehousing and Data mining: an Introduction Federico Facca, Alessandro Gallo, federico@grafedi.it sciack@virgilio.it

More information

University of Gaziantep, Department of Business Administration

University of Gaziantep, Department of Business Administration University of Gaziantep, Department of Business Administration The extensive use of information technology enables organizations to collect huge amounts of data about almost every aspect of their businesses.

More information

Module Title: Business Intelligence

Module Title: Business Intelligence CORK INSTITUTE OF TECHNOLOGY INSTITIÚID TEICNEOLAÍOCHTA CHORCAÍ Semester 1 Examinations 2012/13 Module Title: Business Intelligence Module Code: COMP8016 School: Science and Informatics Programme Title:

More information

Understanding Data Warehousing. [by Alex Kriegel]

Understanding Data Warehousing. [by Alex Kriegel] Understanding Data Warehousing 2008 [by Alex Kriegel] Things to Discuss Who Needs a Data Warehouse? OLTP vs. Data Warehouse Business Intelligence Industrial Landscape Which Data Warehouse: Bill Inmon vs.

More information

Adapting an Enterprise Architecture for Business Intelligence

Adapting an Enterprise Architecture for Business Intelligence Adapting an Enterprise Architecture for Business Intelligence Pascal von Bergen 1, Knut Hinkelmann 2, Hans Friedrich Witschel 2 1 IT-Logix, Schwarzenburgstr. 11, CH-3007 Bern 2 Fachhochschule Nordwestschweiz,

More information

Business Intelligence and Column-Oriented Databases

Business Intelligence and Column-Oriented Databases Page 12 of 344 Business Intelligence and Column-Oriented Databases Kornelije Rabuzin Faculty of Organization and Informatics University of Zagreb Pavlinska 2, 42000 kornelije.rabuzin@foi.hr Nikola Modrušan

More information

The Applications of Business Intelligence to the Improvement of Supply Chain Management A Case of an Electronic Company

The Applications of Business Intelligence to the Improvement of Supply Chain Management A Case of an Electronic Company JOURNAL OF SOFTWARE, VOL. 6, NO. 11, NOVEMBER 2011 2173 The Applications of Business Intelligence to the Improvement of Supply Chain Management A Case of an Electronic Company Chwei-Jen Fan Dept. of Information

More information

Oracle BI 11g R1: Create Analyses and Dashboards

Oracle BI 11g R1: Create Analyses and Dashboards Oracle University Contact Us: Local: 1800 103 4775 Intl: +91 80 67863102 Oracle BI 11g R1: Create Analyses and Dashboards Duration: 5 Days What you will learn This Oracle BI 11g R1: Create Analyses and

More information

A PANEL STUDY FOR THE INFLUENTIAL FACTORS OF THE ADOPTION OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEM

A PANEL STUDY FOR THE INFLUENTIAL FACTORS OF THE ADOPTION OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEM 410 International Journal of Electronic Business Management, Vol. 4, No. 5, pp. 410-418 (2006) A PANEL STUDY FOR THE INFLUENTIAL FACTORS OF THE ADOPTION OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEM Jan-Yan

More information

Data Warehousing and Data Mining in Business Applications

Data Warehousing and Data Mining in Business Applications 133 Data Warehousing and Data Mining in Business Applications Eesha Goel CSE Deptt. GZS-PTU Campus, Bathinda. Abstract Information technology is now required in all aspect of our lives that helps in business

More information

A Framework for Developing the Web-based Data Integration Tool for Web-Oriented Data Warehousing

A Framework for Developing the Web-based Data Integration Tool for Web-Oriented Data Warehousing A Framework for Developing the Web-based Integration Tool for Web-Oriented Warehousing PATRAVADEE VONGSUMEDH School of Science and Technology Bangkok University Rama IV road, Klong-Toey, BKK, 10110, THAILAND

More information

Strategy for Selecting a Business Intelligence Solution

Strategy for Selecting a Business Intelligence Solution Revista Informatica Economică nr. 1(45)/2008 103 Strategy for Selecting a Business Intelligence Solution Marinela MIRCEA Economy Informatics Department, A.S.E. Bucureşti Considering the demands imposed

More information

Why include analytics as part of the School of Information Technology curriculum?

Why include analytics as part of the School of Information Technology curriculum? Why include analytics as part of the School of Information Technology curriculum? Lee Foon Yee, Senior Lecturer School of Information Technology, Nanyang Polytechnic Agenda Background Introduction Initiation

More information

Issues in Information Systems Volume 15, Issue I, pp. 277-284, 2014

Issues in Information Systems Volume 15, Issue I, pp. 277-284, 2014 BEST PRACTICES FOR SUCCESSFUL DEVELOPMENT OF DATA WAREHOUSES FOR SMALL BUSINESSES Ángel Ojeda-Castro, Universidad del Turabo, Gurabo, PR, ut_aojeda@suagm.edu Mysore Ramaswamy, Southern University, Baton

More information

SENG 520, Experience with a high-level programming language. (304) 579-7726, Jeff.Edgell@comcast.net

SENG 520, Experience with a high-level programming language. (304) 579-7726, Jeff.Edgell@comcast.net Course : Semester : Course Format And Credit hours : Prerequisites : Data Warehousing and Business Intelligence Summer (Odd Years) online 3 hr Credit SENG 520, Experience with a high-level programming

More information

Business Intelligence: The European Perspective

Business Intelligence: The European Perspective Markets, F. Buytendijk Research Note 5 November 2002 Business Intelligence: The European Perspective When choosing business intelligence products, European users are not that different from North American

More information

Customer Relationship Management based on Increasing Customer Satisfaction

Customer Relationship Management based on Increasing Customer Satisfaction International Journal of Business and Social Science Vol. 5, No. 5; April 2014 Customer Relationship Management based on Increasing Customer Satisfaction Fangfang Tao Management School Shanghai University

More information

C A S E S T UDY The Path Toward Pervasive Business Intelligence at an International Financial Institution

C A S E S T UDY The Path Toward Pervasive Business Intelligence at an International Financial Institution C A S E S T UDY The Path Toward Pervasive Business Intelligence at an International Financial Institution Sponsored by: Tata Consultancy Services October 2008 SUMMARY Global Headquarters: 5 Speen Street

More information

Microsoft Data Warehouse in Depth

Microsoft Data Warehouse in Depth Microsoft Data Warehouse in Depth 1 P a g e Duration What s new Why attend Who should attend Course format and prerequisites 4 days The course materials have been refreshed to align with the second edition

More information

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers 60 Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative

More information

White Paper The Benefits of Business Intelligence Standardization

White Paper The Benefits of Business Intelligence Standardization White Paper The Benefits of Business Intelligence Standardization Why Should You Standardize Your Business Intelligence Tools? Author: Timo Elliott (timo.elliott@businessobjects.com) Contributors: Audience:

More information

An Approach for Facilating Knowledge Data Warehouse

An Approach for Facilating Knowledge Data Warehouse International Journal of Soft Computing Applications ISSN: 1453-2277 Issue 4 (2009), pp.35-40 EuroJournals Publishing, Inc. 2009 http://www.eurojournals.com/ijsca.htm An Approach for Facilating Knowledge

More information

Hybrid Support Systems: a Business Intelligence Approach

Hybrid Support Systems: a Business Intelligence Approach Journal of Applied Business Information Systems, 2(2), 2011 57 Journal of Applied Business Information Systems http://www.jabis.ro Hybrid Support Systems: a Business Intelligence Approach Claudiu Brandas

More information

Keynote: How to Implement Corporate Performance Management (CPM), Pervasive BI & ROI: Hard & Soft

Keynote: How to Implement Corporate Performance Management (CPM), Pervasive BI & ROI: Hard & Soft Atre Group, Inc. Keynote: How to Implement Corporate Performance Management (CPM), Pervasive BI & ROI: Hard & Soft Shaku Atre Atre Group, Inc. 2222 East Cliff Drive, Suite#216 Santa Cruz, CA 95062 831.460.9300

More information

BUSINESS INTELLIGENCE COMPETENCY CENTER

BUSINESS INTELLIGENCE COMPETENCY CENTER BUSINESS INTELLIGENCE COMPETENCY CENTER Last Updated: December 2012 Dr. Joseph M. Woodside Executive Director BICC, Stetson University Dr. Ted J. Surynt Executive Advisory Board, Stetson University Dr.

More information

Data Warehouse: Introduction

Data Warehouse: Introduction Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of base and data mining group,

More information

Successful BI Survey. Best practices in business intelligence for greater business impact. www.biscorecard.com. By Cindi Howson 2014 ASK LLC

Successful BI Survey. Best practices in business intelligence for greater business impact. www.biscorecard.com. By Cindi Howson 2014 ASK LLC www.biscorecard.com 2014 Successful BI Survey Best practices in business intelligence for greater business impact By Cindi Howson 2014 ASK LLC February 2014 Table of Contents Background... 4 Copyright

More information

Key organizational factors in data warehouse architecture selection

Key organizational factors in data warehouse architecture selection Key organizational factors in data warehouse architecture selection Ravi Kumar Choudhary ABSTRACT Deciding the most suitable architecture is the most crucial activity in the Data warehouse life cycle.

More information

Understanding The Concept Of Business Intelligence In Slovak Enterprises

Understanding The Concept Of Business Intelligence In Slovak Enterprises Understanding The Concept Of Business Intelligence In Slovak Enterprises Ing. Anna Hamranová, Ing. Anita Romanová, PhD. Ekonomická univerzita v Bratislave, Fakulta podnikového manažmentu, Katedra informačného

More information

Leader s Interpersonal Skills and Its Effectiveness at different Levels of Management

Leader s Interpersonal Skills and Its Effectiveness at different Levels of Management International Journal of Business and Social Science Vol. 3 No. 4 [Special Issue - February 2012] Leader s Interpersonal Skills and Its Effectiveness at different Levels of Management Aamir Khan Dr. Wisal

More information