Top PDF Making the Case for a Business Intelligence Framework

Making the Case for a Business Intelligence Framework

Making the Case for a Business Intelligence Framework

introduces the idea of “live documents” and states that these documents “require an authoring framework that frees the author from any implementation tasks” (245) which shows a very good parallel to a project manager using a dashboard within a pre-defined framework. Kret seems to have the best list of “reasons” as to why a dashboard would be used as opposed to standardized reports (59) and his research shows how a dashboard would fit into an IT architecture as a support system interface (Kret 61). Mille uses a similar design for an example dashboard in his architecture (Mille S817) and gives a reasonable definition: “We name dashboard a window containing views where each one represents any kind of information (variables, images, texts, video, ties between
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Issues and challenges in business intelligence case studies

Issues and challenges in business intelligence case studies

Business Intelligence (BI) has embarked on decision-making setting. This has influenced many organizations from different industries that are located in diverse regions to implement BI. Critical Successful Factors (CSF) becomes the guideline for the implementer to adopt BI successfully. However, lack of BI knowledge and weak consideration of BI CSF led to the failure of BI implementation project. Several issues and challenges have been identified during the BI implementation. In addition, other researchers rarely discussed this subject. Thus, the objective of this paper is to recognize the issues and challenges on BI implementation. Through qualitative method, BI practices systematically described the purpose of BI execution on selected organizations, industries and regions. It has given the path towards the issues and challenges of BI implementation. The identified issues and challenges are defining the business goal, data management, limited funding, training and user acceptance as well as the lack of expertise issues. The findings categorized the issues and challenges into three dimensions of CSF for BI implementation, which are Organization, Process and Technology dimension. Limitation in this study requires future researchers to study in details of these issues and challenges including the solutions and the impact of BI implementation.
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A Framework for Telemedicine Care: A Case of Nandi  County – Kenya

A Framework for Telemedicine Care: A Case of Nandi County – Kenya

Abstract:- Telemedicine is one of the technologies that use the knowledge of Information Communication Technologies (ICTs) to curb geographical barriers while increasing access to healthcare services. This study aimed developing a framework for telemedicine care in Kenya. This study was done in health facilities in Nandi County. The specific objectives of the study were: To examine emergency healthcare need suitable for telemedicine care in Nandi County -Kenya; to analyze the readiness for telemedicine care and to design a suitable telemedicine care framework. This study was conducted using cross- sectional descriptive survey research design. The study sampled 4 doctors, 59 nurses, 12 clinical officers, 1 pharmacist and 4 pharmaceutical technologists, making it a sample size of 80 from target population of 650 healthcare workers working at the County hospital two sub county hospitals and 2 health centres. Structured questionnaire and a focused group discussion guide were used to collect the data. Pilot testing for the instruments were done to ascertain to improve on face and content validities. The data collected was analyzed using SPSS software version 20 where both descriptive statistics on emergency healthcare need levels for telemedicine care and the readiness for telemedicine care were computed. Analyzed results were presented using table, pie-chart and bar graphs. From the findings it was evident that 77.5% of the respondents supported that specialist referral services are critically needed. With respect to direct patient care services 82.5% of them supports that these services are critical, 53.8% of the respondents accepted that medical education and mentoring is a critical emergency healthcare need. Concerning remote patient monitoring, 45% of the respondents agreed that it is a critical healthcare need. 51.3% of the respondents perceive that Tele-nursing is a critical healthcare need and on Tele-Pharmacy, 54.5% of them perceive that it is critical. 20% of all respondents perceive that Tele- radiology is a critical emergency healthcare need, with less than 20% perceiving that it is least critical.
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Understanding RFID Technology within a Business Intelligence Framework

Understanding RFID Technology within a Business Intelligence Framework

Within the context of BI, the better the data, the more accurate are the results of the analytics that employ the data. This in turn leads to more informed and (hopefully) better decision-making [36]. In BI, the ideal means for capturing data is via source automation, since this proc- ess increases both the efficiency and the accuracy of data entry and it is cost effective because it eliminates much of the effort and delay caused when data must be tran- scribed. RFID technology is a source automation vehicle since it provides an automated, efficient, cost-effective means of providing accurate data for BI evidence-based decision making. RFID data is used to build up an “in- ternet of things”, which can be viewed as a network that allows companies to track goods through the global sup- ply chain and execute many applications simultane- ously [37]. In addition, RFID source automation capa- bilities deliver data that BI can use to prevent potential economic damage caused by product piracy. This is pos- sible because RFID tag data is effectively used for prod- uct authentication in the supply chain [38].
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A business intelligence framework for 
		Higher Education Institutions

A business intelligence framework for Higher Education Institutions

People is classified in this framework as a variety of users in university which have different roles and functions in analytics, business and decision processes [7]. Additionally, these users also require different types of analysis, delivery of information and data. According to Jusoh, et al. [27], the people involved in this framework are the corresponding users who are involved in academic and non-academic management such as university’s top management, administrative and academic staffs, hostel supervisors and students. The way people perform their role in the university is changing. Today, people can no longer sit, restrict and control the flow of information within the university. This information must be made available to the people if the information is very important for them to make important decisions for the university. Sometimes different types of users require the same information in different ways. For example the way information is to be delivered should be customized [28]. People in this framework is specified as users involved with vision and mission and also organization strategy development as mentioned by Cates, et al. [17] in LOBI framework. Thus if possible, people who involved in this framework is able to see instantly the information that is relevant for them. In the HEIs environment, process is an activity which transform the large volumes of data available in university into information and knowledge for the top management to make the effective decision making [29].
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Financial Accounting Fraud Detection Using Business Intelligence

Financial Accounting Fraud Detection Using Business Intelligence

Based on the information and analysis gained from Phase 1 and Phase 2, this investigative analysis phase involves pattern evaluation, performing validations of the results, fraud symptoms and scheme mapping as well as use of industry metrics and error rates as benchmarks for identifying the fraud schemes and their severity. The auditors and the management should be able to perform automated visual walkthroughs to locate and correct anomalies. The results obtained in this phase would serve as meaningful feedback for the organisation to make improvements in their business practices, procedure, policies and control mechanisms. While traditional approaches are also aimed at achieving this, such approaches are constrained by time, technical knowledge and investigative experience of forensic accountants, requiring adoption of artificial intelligence techniques such as neural networks (Spathis et al., 2002; Lin et al., 2003; Kapardis et al., 2010). In addition to automation and accuracy that results in timely fraud detection and improved decision making, our business intelligence framework adopts a feedback loop as shown in Figure 1 to follow through the three phases of analysis as part of continuous improvement in arriving at the industry specific best accounting practices.
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A Scalable Business Intelligence Decision Making System in the Era of Big Data

A Scalable Business Intelligence Decision Making System in the Era of Big Data

Data integration is a major step in the decision-making process and is responsible for storing data from disparate and diverse sources for decision making. Several approaches have emerged to address data integration issues including those related to data sources. Among these approaches are ETL Extract Transform Load [1], EAI Enterprise Integration Application and EII Enterprise Information Integration. The ETL approach is often used in the case of a large amount of data from different sources that must undergo complex transformations. As for the EII approach is recommended in the case of an already existing data warehouse with the possibility of linking it to data sources of a medium volume. While the EAI approach ensures the integration of data from non-accessible sources directly and storing a small amount of data [2].
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IMPROVING PERFORMANCE OF BUSINESS INTELLIGENCE THROUGH CASE BASED REASONING

IMPROVING PERFORMANCE OF BUSINESS INTELLIGENCE THROUGH CASE BASED REASONING

 Decision making &Action after analyzing information, decision is being made. At this stage, the cycle stops and action is taken. Then action is taken based on your analysis. Once you have acted, it's a good idea to evaluate the results of your actions and determine what new intelligence needs have developed. The Business Intelligence (BI) can only be culled from complete information - information that spans across the range of functional silos that make up the enterprise, organizes for clarity and reliability, provides true decision support, and lays the base for competitive superiority and action. It is involved with various applications such like ERP, CRM and SCM applications which organize the vast amount of information for analyzing the business activities. Every decision must be customized to the company’s own requirements and resources.
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Developing and Leveraging Business Intelligence Systems for Decision Making in Organizations

Developing and Leveraging Business Intelligence Systems for Decision Making in Organizations

In recent years, Business Intelligence (BI) has started to play a significant role for businesses regarding of development and helping to increase achievements and supporting decisions making. Factors such as changing, innovation, globalization, and sustainability in changing markets environment accelerate the shift towards using BI. One of the difficulties that are affecting the business world is the increasing volume of data that is everywhere. BI allows for a large amount of data from different sources to be converted into helpful information, knowledge, and insights. This paper explains that the BI systems are not just about tools. Nevertheless, it is a wide range of applications and processes not for getting data out of the warehouse, but also for getting data into a warehouse, and for visualizing the trend in the data. This paper aims to investigate the concepts of BI, its framework, the relationship between BI and DSS, benefits of BI, its applications, its software and tools, and finally issues of implementation BI.
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A Proposed Framework for Detecting and Predicting Diseases through Business Intelligence Applications

A Proposed Framework for Detecting and Predicting Diseases through Business Intelligence Applications

The motivation of addressing the research problem comes from that Diabetes is one of the major health problems in Egypt where According to DR. Hesham elHefnawy “The Dean of the National Institute of Diabetes” people who are suffering from the diabetes in Egypt are more than 7 million patients and it expected to increase exponentially in the upcoming years so we need to make an early detection for this disease. Diabetes not only affect the patients, but it also leads to losses in the state budgets because of the costs resulting from diagnosing and treatment of the disease and this cost increases in the case of disease progression and lead to a lot of complications such as kidney failure where the dialysis itself costs a lot from the overall state’s budget.
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A FRAMEWORK FOR BUSINESS INTELLIGENCE APPLICATION USING ONTOLOGICAL CLASSIFICATION

A FRAMEWORK FOR BUSINESS INTELLIGENCE APPLICATION USING ONTOLOGICAL CLASSIFICATION

Business Intelligence (BI) solutions offer the means to transform data into information and derive knowledge through analytical tools in order to support decision making. Analytical tools should support decision makers to find the right information quickly and enable them to make well-informed decisions. Business intelligence (BI) is the process of gathering enough of the right information in the right manner at the right time, and delivering the right results to the right people for decision-making purposes so that it can continue to yield real business benefits, or have a positive impact on business strategy, tactics, and operations in the enterprises.[4]Business Intelligence (BI) is defined as an integrated set of tools to support the transformation of data into information in order to support decision making.[2]
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From Management Information Systems to Business Intelligence: The Development of Management Information Needs

From Management Information Systems to Business Intelligence: The Development of Management Information Needs

The recent research on complex information needs including decision support and business intelligence has been diversified into quite a few related areas; far from being an exhaustive set, several examples follow. Lemieux and Dang [7] have researched the issues of accountability for decision making, and suggested tools for tracking the decision-making reasoning of human agents, thus adding to the research on a problem of experience management. Thorleuchter and Van den Poel [17] have investigated the use of website content analysis in partner search for improved research and technology collaboration planning, adding to the body of research on information integration. Saad et al [11] have researched a conceptual framework for early warning information systems for crisis situations, expanding the research on intelligence technologies for monitoring and detection. Castano [1] has researched the possibility of putting together business process management (BPM) and data mining techniques to provide intelligent BPM management functions. Redondo-Garcia et al [10] have researched information integration tasks when using disparate (heterogeneous) information sources.
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Business Intelligence - A Gift for Decision Maker for the Effective Decision Making

Business Intelligence - A Gift for Decision Maker for the Effective Decision Making

ABSTRACT: Business Intelligence is a socio-technical concept emerged to help managers especially in their decision making tasks. A manager with different decision making styles has been started to make use of business intelligence in their own ways. Are the all managers taking benefits of Business intelligence in the same way? Does Business intelligence give each category what they want in the decision making process? If the answer to these questions is – No, then what is the expectation of managers from BI having different decision making style? Will BI could satisfy their needs? If yes, then how? By using well-formed theory in different styles of decision making and taking BI capabilities into consideration this paper highlights the framework which defines appropriate BI capabilities with each decision making style. Study shows in order to serve each style of decision in which BI capabilities changes with respect to style. It is believed that by making BI customized based on decision making styles; BI would be the much more successful in serving all the categories of managers.
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A Comprehensive Diagnostic Framework for Evaluating Business Intelligence and Analytics Effectiveness

A Comprehensive Diagnostic Framework for Evaluating Business Intelligence and Analytics Effectiveness

As organizations continue to make ever-larger investments in BIA capabilities to support an expanding array of organizational decision making activities, effective and efficient approaches for BIA capability assessment becomes an essential tool. Leveraging a design science approach, this paper presents a practical and useful framework and toolkit for this specific purpose. Per Hevner’s first design science guideline, we developed two artefacts – a comprehensive BIA effectiveness diagnostic (BIAED) framework (i.e., a model) and an online diagnostic toolkit (i.e., an instantiation). The framework encompasses three main perspectives: the coverage of effectiveness dimensions; the process context for assessment; and the constituencies from whom input must be sought. This research addresses the problem of efficiently diagnosing the effectiveness of current state BIA capabilities across critical dimensions from the perspective of multiple stakeholder groups which is a critical (unaddressed) problem for many organizations today, thus conforming to Hevner’s second guideline - problem relevance. We designed novel artefacts that have been informed by, and incorporate elements of, previously developed maturity models practically test their efficacy through large-scale deployment and evaluation in three organizations (Hevner et al.’s Guideline 5 – research rigor).
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Design of Integrated Business Intelligence System Framework for Insurance Business Processes

Design of Integrated Business Intelligence System Framework for Insurance Business Processes

Business intelligence is a key means to promote core competence of enterprise. The high construction cost of business intelligence severely limits the popularization and development of business intelligence system. Business process management (BPM) is a key business initiative that enables companies to align strategic and operational objectives with business activities in order to fully manage performance through better informed decision making and action. Effective business performance requires an organization to model and monitor not only its tactics but also its strategies and the assumption on which these strategies are built. Decision making is an important task for enterprise managers, and is typically based on various data sources derived from information systems, such as enterprise resource planning, supply chain management and customer relationship management. Numerous business intelligence tools (BI) thus have been developed to support decision making. Some existing BI tools have several limitations, for example lacking data analysis and visualization capabilities. The aim of this paper is to examine the processes, methodologies and technologies underlying BPM in insurance, the relation between BPM and business intelligence, and to propose a framework for integrating corporate performance management and business intelligence.
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ASSESSING THE EFFECTIVENESS OF BUSINESS INTELLIGENCE IN MONITORING PERFORMANCE OF PALM OIL PLANTATION

ASSESSING THE EFFECTIVENESS OF BUSINESS INTELLIGENCE IN MONITORING PERFORMANCE OF PALM OIL PLANTATION

The business intelligence plantation performance system starts with the stages of data integration, data analysis, making reports, creating a web dashboard and then integrating the web dashboard with the web portal. Data analysis is processed with OLAP and data mining to extract information from data stored in the data warehouse. The results of the data analysis process are represented in the form of statistical reports and dashboards, then used as supporting decisions for oil palm plantations. This study is focus on design palm plantation business intelligence systems for decision support oil palm plantation at PT DSN Group web based OLAP. This research produces a system framework and web portal for business intelligence systems that are accessed through an intranet browser. Business Intelligence can be used as a solution to consider the decision-making process in the management of oil palm plantations and solutions in increasing plantation productivity to achieve Target Plantation Performance.
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Selecting and evaluating a benefits management method for IT projects

Selecting and evaluating a benefits management method for IT projects

The benefits management deployment plan is developed in this study. It is based on the optimized Cranfield method, findings from the case study at Philips and findings from interviews at HNL. The Philips case study findings can be generalized for use at HNL, because the companies are similar in many ways. Philips has a turnover, an amount of employees and an amount of operating countries in the same order of magnitude as Heineken and they both have innovation, sustainability and marketing in the center of their strategy. The findings from HNL interviews can be generalized for use at HNL, because of the large amount of interviewees (thirty-eight people) and the differentiation in interviewees (people from IT HNL, the finance department and several business departments). The sources for the deployment plan are all internally valid for use at HNL. The deployment plan (including the optimized Cranfield method) is tested in two pilot projects. The pilots are executed at HNL (in the Commerce and the Supply departments) with people from IT HNL, the finance department and the business departments. Having pilots in two departments with people from several departments strengthens the internal validity of the pilot results. However, the amount of pilots (two pilot projects, one of which was only partially finished) weakens the internal validity. The lessons learned when testing the deployment plan have a limited internal validity, but they do give a good indication of the applicability of the deployment plan.
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Relationship between Business Intelligence and Supply Chain Management for Marketing Decisions

Relationship between Business Intelligence and Supply Chain Management for Marketing Decisions

Marketing decision making should perform the function of maximizing the perception of the value of business entity market supply. The efficiency of data collection and analysis of competition in this sense are the imperative. Some authors define this process as market mechanism (Kotler) – Competitor Intelligence System. The already mentioned research suggests that CIS should be adjusted to the company and the environment in which it operates. Positive experiences indicate a convenience of Business Intelligence analysis for making marketing decisions through five levels: 1. Early warning intelligence related to unusual market
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Foreign direct investment in the Indian telecommunications sector

Foreign direct investment in the Indian telecommunications sector

There were several variables that were not included in the regression model due to a lack of data. These variables include the number of days it takes to open a new business (representing the regulatory and legal environment), the reliability and safety of the public transportation network (rail, bus and air transport), the amount of students graduating from secondary and tertiary educational institutions (to represent the skill level of the labor force).

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The Future Scope of Business Intelligence (BI)

The Future Scope of Business Intelligence (BI)

In today’s increasingly complex economy, there is more to business than simple calculations based on speculative analysis. Companies need access to relevant, accurate data in order to keep up with the consumer market trends that will dictate their actions as a business. As complexity within the global marketplace grows, it becomes increasingly difficult to keep up with all the pertinent information that requires the attention of business owners. [6] This means that new ways of thinking about intelligence must be considered in order to adapt to the constant changes in consumerism. Fortunately, the very technologies that have promoted the economic complexity of this day and age have also supplied businesses with the ability to access this information easily and without hassle. Software programs can help business owners connect the various specialized fields within a company in order to bring about a clear view of the enterprise as a whole. Marketing information, logistical data, supply and demand numbers, and other indispensable components of business can be compared, [7]viewed side by side, and presented in a way that translates numbers into meaningful data.
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