...implementation of a business intelligence (BI) system is a complex undertaking requiring considerable resources. Yet there is a limited authoritative set of critical success factors (CSFs) for management reference because the BI market has been driven mainly by the IT industry and vendors. This research seeks to bridge the gap that exists between academia and practitioners by investigating the CSFs influencing BI systems success. The study followed a two-stage qualitative approach. Firstly, the authors utilised the Delphi method to conduct three rounds of studies. The study develops a CSFs framework crucial for BI systems implementation. Next, the framework and the associated CSFs are delineated through a series of case studies. The empirical findings substantiate the construct and applicability of the framework. More significantly, the research further reveals that those organisations which address the CSFs from a business orientation approach will be more likely to achieve better results. Keywords: Business intelligence system, Critical success factors, Delphi method, Case study INTRODUCTION Recently Business Intelligence (BI) applications have been dominating the technology priority list of many CIOs [11, 12]. According to Reinschmidt and Francoise [22], a BI system is “an integrated set of tools, technologies and programmed products that are used to collect, integrate, analyse and make data available”. Stated simply, the main tasks of a BI system include “intelligent exploration...
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...Intelligence (BI) Index of Topics covered 1 What is BI 2 Applications of BI 3 Common Functions of BI 4 Requirement & Challenges of BI Implementation 5 Best Practices of BI 6 Case Study 7 Conclusion What is BI: BI is a broad category of applications and technology for gathering, storing and providing access to data to help enterprises make better decisions. It can provide information of various “Information Assets” in an organization and how they interact with each other. These assets include Customer Databases, SCM Information, Personnel data, Manufacturing, Sales & Marketing Activity. Applications of BI: BI can be applied to MARCKM * Measurement - performance metrics, benchmarking etc., * Analytics - data mining, process mining, predictive modeling * Reporting - Data visualization, Executive Information System * Collaboraton - Data sharing & Electronic Data Interchange. * Knowledge Management - This leads to regulatory compliance and learning management The term was used by Gartner group in 1996, “..... Data analysis, reporting and query tools can help business users wade through a sea of data to synthesize valuable information from it - which today collectively fall into a category of BI.” Common Functions & Requirements of BI Common functions of BI are reporting, analytics, data mining, process mining, complex event processing and predictive analysis. Requirement & Challenges of BI Implementation ...
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...Jacob Moore GBA 673 Business Intelligence Jacob Moore GBA 673 Dr. Lara Preiser-Houy, CDP August 20th, 2013 1|Page Jacob Moore GBA 673 Table of Contents Abstract ....................................................................................................................................................... 3 Introduction ............................................................................................................................................... 3 Background ................................................................................................................................................ 4 Conceptualization ..................................................................................................................................... 4 BI 1.0 ......................................................................................................................................................... 4 BI 2.0 ......................................................................................................................................................... 5 BI 3.0 ......................................................................................................................................................... 5 Opportunities ............................................................................................................................................ 6 Challenges ........................................
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...Real World Activities 1. There are two “traditionally” known methods of the use of Business Intelligence (BI), these are “mere” reporting and transformational. Initially, the goal of BI was in the reporting, taking raw data that the organization collected over a given period of time and converted it into a meaningful representation. This enables organization to see things such as statistics on sales happening in a specific region during a given timeframe. This is what we see in Hillman Group’s use of BI where they tracked information on customer orders, but didn’t use it to make any changes. Next the business requirements for organizations use of data changed to the push to streamline business processes which lead to Transformational BI. In the case study we saw the use of transformational BI through Avnet and Quaker Chemical as a way to generate sales and collect on overdue accounts. We see the differences between reporting and transformational BI being that reporting is concerned mostly concerned with providing information whereas transformational is focused on using the information that is provided. One example I found of the use of BI is a hotel franchise using data on room occupancy, room rates to determine revenues generated, this differs from the implementations of BI in the case study as it is focused on just reporting and not using the information in a transformational way. Another example is a bank that bridges a legacy database with departmental databases, giving...
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...companies do, by using long formulas on a spreadsheet which could sometimes take hours to collect to get what could be accurate information. While looking through some businesses that have implemented BI (Business Intelligence) into their company, I was able to determine that they all became more efficient and in the end used less man hours getting information that they were looking for. Some businesses try collecting business information and it comes from a variety of different places and sources, to be put together in one area. This for one takes time to gather and two is much less efficient, requiring more people and more hours, causing a company to lose money. Sometimes the information may not be entirely accurate as well because of how long it takes to gather up and by the time they get the information they are looking for it is already out of date. In the end business intelligence eliminates "guess work" which a lot of higher-up in businesses have to do sometimes because of their business lacking the data structure to get the information needed. Another thing BI would do is help a company answer and decide situations much faster because they are able to get the information needed much quicker and more effectively. Another big thing that a company can implement and utilize in BI would be getting an insight on customer behavior which could help a company turn this new knowledge into more profit. To give some examples of some of the businesses that...
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...Management (KM), either in a tacit or explicit form, plays an important role in decision making. Business Intelligence (BI) has acquired significant importance in the business world due to the recent technological advancements and availability of state-of-theart software tools. Presently, most of the organizations across the globe are adopting BI solutions to promote business, retain customers, earn maximum profits, reduce recurring expenditures, etc. KM, on the other hand, has not gained significant acknowledgement from an implementation perspective. Moreover, the effect of BI on KM and vice versa is rarely observed. In this paper, we propose a model where KM and BI can benefit from each other. Since both of the said fields have a wide range of features, the proposed model is based on specific features. For that purpose, we have identified a number of Critical Success Factors (CSFs) related to both BI and KM technologies reported in contemporary research. Afterwards, we have drawn a comparison pertinent to the effectiveness of these CSFs with the similar research studies. The comparison shows that our model that combines both BI and KM technologies is more useful as compared to their individual utilization. Keywords: Business Intelligence, Knowledge Management, Tacit Knowledge, Decision Making, Decision Support Systems, Organizational Learning 1. Introduction It has been observed that the society we live in is gradually turning into...
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...General Business Environment (Monetary and Fiscal Policies) THE INFLUENCES OF BI RATES AND EXPORT TAXES ON INDONESIAN PALM OIL INDUSTRY Prof. Wihana Kirana Jaya, M.Soc.Sc., Ph.D. by: Nanang Suko Sadono 13/361118/PEK/19272 Batch 63 International MAGISTER OF MANAGEMENT UNIVERSITAS GADJAH MADA YOGYAKARTA 2014 THE INFLUENCES OF BI RATES AND EXPORT TAXES ON INDONESIAN PALM OIL INDUSTRY 1. INTRODUCTION Indonesia is the biggest producer of Crude Palm Oil (CPO) in the world which produced more than 25 million tons in 2012 and more than 200 trillion rupiahs in foreign exchange. The development of this industry, therefore, is important for the development of economy in Indonesia, as one tool to deal with problems faced such as poverty. This industry is also crucial in supporting the government in anticipating crisis of energy in the future due to the decreasing number of gas and oil over time. The increasing needs of renewable energy as the substitute of petroleum has also driven the demand of pam oil in international market. This high demand has led the price of palm oil in international market become higher. The high international price then persuade domestic producers to market their products to other countries, and this is a logic consequence since the companies as business entities always want to maximize their profit. The problem arise when all companies are forgetting the domestic market. Cooking oil, which is the end product of CPO, can be said...
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...Deshpande et al., IJPSR, 2011; Vol. 2(10): 2534-2544 IJPSR (2011), Vol. 2, Issue 10 ISSN: 0975-8232 (Review Article) Received on 15 June, 2011; received in revised form 23 September, 2011; accepted 28 September, 2011 BI-LAYER TABLETS- AN EMERGING TREND: A REVIEW Rohan D. Deshpande*1, D. V. Gowda 1, Nawaz Mahammed 1 and Deepak N. Maramwar 2 Department of Pharmaceutics, JSS College of Pharmacy, JSS University 1, S. S. Nagar, Mysore-15, Karnataka, India Karnataka College of Pharmacy 2, Bidar-585401, Karnataka, India ABSTRACT Keywords: Bilayer tablet, Layer separation, Insufficient hardness, Individual layer weight control Correspondence to Author: Rohan D. Deshpande Department of Pharmaceutics, JSS College of Pharmacy, JSS University, S.S. Nagar, Mysore-15, Karnataka, India Bi-layer tablets have been developed to achieve controlled delivery of different drugs with pre-defined release profiles. In the last decade, interest in developing a combination of two or more Active Pharmaceutical Ingredients (API) in a single dosage form (bilayer tablet) has increased in the pharmaceutical industry, promoting patient convenience and compliance. Bilayer tablets can be a primary option to avoid chemical incompatibilities between API by physical separation, and to enable the development of different drug release profiles (immediate release with extended release). Despite their advantages, due to the use of different materials and complex geometric boundaries between the adjacent...
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...ASSESSMENT ITEM 1—WRITTEN ASSIGNMENT Due date: Weighting: Length: Week 6 40% Less than 5MB ASSESSMENT 1 OBJECTIVES This assessment item related to course learning outcomes 1, 2 and 6. QUESTION 1 (5 MARKS) List and describe the major components of BI. What are the major similarities and differences between DSS and BI? QUESTION 2 (20 MARKS) XYZ is a manufacturing company specialising in a variety of dairy products. The company is planning to launch a new product in the Australian market. The product development group claims that the anticipated net present value for the new product is over $1,000,000 (one million dollars) and they have recommended the project to proceed. Your task is to check the group‟s claim to determine if it is reasonable. In doing so, you are required to develop a decision support system using Visual DSS. This decision support system will be used to assist the management of the company to make an informed decision about manufacturing of the new product. Table 1 summarises the related information. Cost of production: $7.25 per unit Annual overhead cost: $1,000,000 Initial investment needed: $5,000,000 Estimated selling price: $15.75 per unit Market at time of introduction: 900,000 units per year Market growth: 9.5% per year Market share: 36% Assumed economically useful lifetime: 5 years, commencing in 2014 Discount rate used to analyse new product proposals is 12% Table 1: Production details 1 Your task details: 1. Develop a DSS...
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...|BUSINESS INTELLIGENCE |Week 1 & 2 | |Diploma in IT | | |Year 3 (2013/14) Semester 6 | | | |2 hours | |Introduction to Business Intelligence | OBJECTIVES 1. Define Business Intelligence & describe the architecture 2. Describe the Business Intelligence Process 3. Explain Business Intelligence architecture and implementation issues Part 1: Review Questions 1. Define BI. Business Intelligence (BI) is the process of gathering information in the field of business. It can be described as the process of enhancing data into information and then into knowledge. Business Intelligence is carried out to gain sustainable competitive advantage, and is valuable core competence in some instances. 2. List and describe the major components of BI. 1) A data warehouse, with its source data 2) Business analytics, a collection of tools for manipulating, mining, and analyzing the data in the data warehouse; 3) Business Performance Management (BPM)...
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...Decision support systems and Business Intelligence: an overview Contents Course introduction 1–3 Module one objectives 1–3 Use of Study Guide 1–3 Suggested study schedule 1–4 Readings 1–4 Changing business environments and computerised decision support 1–4 Managerial decision-making 1–5 Computerised support for decision making: systems and technologies 1–5 The systems 1–5 The technologies 1–5 A framework for decision support 1–6 Management science 1–6 Concept of decision support systems & business intelligence 1–7 DSS – BI connection 1–7 Course plan and themes 1–7 Conclusion 1–8 Course introduction This first module aims to provide an overview of the topic and provide the broad backdrop into which the other modules will fit. Today’s business environment is constantly changing, and it is becoming more and more complex. Private and public organizations are required to respond quickly to changing conditions; be it government regulations or informed customers or market conditions. This requires organizations to be agile and to make frequent and quick strategic, tactical, and operational decisions. Making such decisions may require considerable amounts of relevant data, information, and knowledge. Processing these, in the framework of the needed decisions, must be done quickly, frequently in real time, and usually requires some computerized support. This course is about using business intelligence as computerized support for managerial...
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...zongpeng}@ucalgary.ca of Computer Science, The University of Hong Kong, cwu@cs.hku.hk † Department Abstract—This work studies resource allocation in a cloud market through the auction of Virtual Machine (VM) instances. It generalizes the existing literature by introducing combinatorial auctions of heterogeneous VMs, and models dynamic VM provisioning. Social welfare maximization under dynamic resource provisioning is proven NP-hard, and modeled with a linear integer program. An efficient α-approximation algorithm is designed, with α ∼ 2.72 in typical scenarios. We then employ this algorithm as a building block for designing a randomized combinatorial auction that is computationally efficient, truthful in expectation, and guarantees the same social welfare approximation factor α. A key technique in the design is to utilize a pair of tailored primal and dual LPs for exploiting the underlying packing structure of the social welfare maximization problem, to decompose its fractional solution into a convex combination of integral solutions. Empirical studies driven by Google Cluster traces verify the efficacy of the randomized auction. I. INTRODUCTION The cloud computing paradigm offers users rapid ondemand access to computing resources such as CPU, RAM and storage, with minimal management overhead. Recent commercial cloud platforms, exemplified by Amazon EC2 [1], Microsoft Azure and Linode [2], organize a shared resource pool for serving their users. Virtualization technologies...
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...RESEARCH REPORT by B. Lekay 2973630 We swear that this assignment is our original work. All information obtained directly or indirectly from other sources has been fully acknowledged. All members of the group contributed equally and fairly to the completion of this project. Signed: BJ Le Kay Date: April 2013 |Table of Contents |Page | |1. Introduction | |1.1 Problem definition and background to the problem |2 | |1.2 Scope and limitations of the report |2 | |1.3 The research question |3 | |1.4 A description of the rest of the report |3 | |1.5 Methodology |3 | |2. Findings derived from the Data Analysis | |2.1 Results pertaining to...
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...yRunning head: Case Study MGMT 221 – Act 1.7 – Assignment: Case Study – J. Burger 0803155 Jacobus J Burger Embry-Riddle Aeronautical University Daytona Beach, Florida Department of Distance Learning Instructor: Amro Saud August 22, 2014 MGMT 221 – Act 1.7 – Assignment: Case Study – J. Burger 0803155 Case Study Questions: 1) a. eCourier : This company uses data processing and analyses software to generate information relevant to their business that manages can act on. They are able to utilize this Business Intelligence resource to more closely and accurately monitor customer satisfaction, increase their customer retention rates and at the same time improve the scalability of their business, without added capital expenditure. They offer an app download on their homepage (eCourier, 2014 ) that allows customers to track the delivery in real-time. On ‘chatting’ with a customer service rep, “Nicola”, the author was informed that eCourier actually offers a customer a real-time video feed of their package from pickup to delivery. This is a unique use of IS technologies and would offer a customer a unique level of customer interaction and service. Utilizing a service such as this would offer a strategic advantage above its competitors. b. Cablecom: This company uses statistical software for data mining and survey creation. They were able to utilize these IS technologies as part of a Knowledge Management and Management Support system....
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...Organizational characteristics Page 1 of 12 18th European Conference on Information Systems BENEFITS AND CHALLENGES OF BUSINESS INTELLIGENCE ADOPTION IN SMALL AND MEDIUM-SIZED ENTERPRISES Scholz, Patrick, HOERBIGER Holding AG / Chemnitz University of Technology, Hannawaldweg 12, 09405 Zschopau, Germany, patrick.scholz@hoerbiger.com / patrick.scholz@wirtschaft.tu-chemnitz.de Schieder, Christian, Chemnitz University of Technology, Thueringer Weg 7, 09126 Chemnitz, Germany, christian.schieder@wirtschaft.tu-chemnitz.de Kurze, Christian, Chemnitz University of Technology, Thueringer Weg 7, 09126 Chemnitz, Germany, christian.kurze@wirtschaft.tu-chemnitz.de Gluchowski, Peter, Chemnitz University of Technology, Thueringer Weg 7, 09126 Chemnitz, Germany, peter.gluchowski@wirtschaft.tu-chemnitz.de Boehringer, Martin, Chemnitz University of Technology, Thueringer Weg 7, 09126 Chemnitz, Germany, martin.boehringer@wirtschaft.tu-chemnitz.de Abstract Leveraging information is a key success factor for companies. Over the last two decades Business Intelligence (BI) has evolved to become a foundational cornerstone of enterprise decision support. However, prior research shows that small and medium-sized enterprises (SMEs), in particular, lag behind in the proliferation of BI. In this exploratory study we examine BI adoption within German SMEs in the state of Saxony (n = 214). We explore perceived benefits and challenges in their efforts to implement BI. By applying cluster analysis to these...
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