Business Intelligence Environment Research Articles

Controllers’ role in managerial sensemaking and information trust building in a business intelligence environment

This study explores how an organization’s controllers (management accountants) give sense to the information provided by its business intelligence (BI) system, and thus shape the construction of information trust. A qualitative case study was conducted within a Finnish food manufacturing company, building on the notion of trust related to management accounting information and sensemaking theory. The study was informed through open-ended interviews and an examination of internal accounting and management reports. The authors found that the company used an integrated BI system that enabled the production of information in a timely and perceivably standardized manner. Controllers managed this accounting information and gave sense to it, helping deliver a shared understanding of the daily business situation. The findings show that controllers play a pivotal role in building information trust by giving sense to the information provided by the BI system.

Analysis of Business Intelligence Systems Transmission Session

Information and Communication Technology (ICT) is the central part of Intelligent systems. Business Intelligence (BI) utilizes ICT resources and capabilities to enhance decision-making from the available information. One of the core components of ICT resources is the network. Hypertext Transfer Protocol (HTTP) is an application layer protocol in a network model responsible for handling "requests" in a transmission session. Transmission Control Protocol (TCP) establishes connections session and keeps track of the state of the communication session. Unfortunately, a request from a critical online transaction over TCP in a BI environment is bound to face some uncertainty. There is a lack of studies on the impact of communication over transmission sessions on BI operations. This paper presented an experimental evaluation of the BI transaction transmission session. Various transactions were performed to monitor and analyze the request made with HTTP over a TCP transmission session. Both the HTTP and TCP features for all transactions were captured. The finding indicates that time is highly associated with less traffic congestion and transaction overhead.

The Use of Business Intelligence Tools to Analyze the Influence of Interactivity and Interaction Factors on the Assessment of Distance Students’ Performance in Virtual Learning Environments

This paper aims to improve the practice of distance education, by providing managers with a view of aspects that influence the progression of students. To that end, it analyses “Interactivity and Interaction” factors in Virtual Learning Environments (VLE) communication systems, seeking to understand how these elements influence the performance of distance learning students at the beginner level. The study was carried out using data from a Brazilian distance learning private university, which utilizes a virtual learning environment. The research involved four steps: construction of a business intelligence environment, statistical analytical work, decision trees and clustering techniques to describe data, establish the most relevant variables and identify standards that may support the conclusion. https://doi.org/10.26803/ijlter.17.9.6

Methods of structural analysis of business processes

The article outlines selected methods for analyzing business processes: their definitions and instances. The methods for analytical processing of processes constitute a component of the Business Intelligence environment - process warehouses, including methods for analytical processing and exploration of the collected process definitions and instances - i.e. process mining. One of the main elements of the analysis of processes is to determine the similarity between them. In systems for analyzing large sets of elements, the method of determining similarity should be efficiency because is the basis for others analysis methods, e.g. clustering, classification, etc. A method for analyzing structural similarity of business processes, based on the similarity of sequences of genetic tags of such processes, was presented using the similarity analysis methods based on the editing distance and the developed methods of structural similarity: GNM, DNM, GCM, DCM. The presented similarity methods were used to clustering processes and to determine the central element of the cluster. The developed methods form the basis for the development of similarity methods extended to aspects of semantic similarity of business processes and methods of analysis and exploration of processes.

MLED_BI: a new BI Design Approach to Support Multilingualism in Business Intelligence

Existing approaches to support Multilingualism (ML) in Business Intelligence (BI) create problems for business users, present a number of challenges from the technical perspective, and lead to issues with logical dependence in the star schema. In this paper, we propose MLED_BI (Multilingual Enabled Design for Business Intelligence), a novel BI design approach to support the application of ML in BI Environment, which overcomes the issues and problems found with existing approaches. The approach is based on a revision of the data warehouse dimensional modelling approach and treats the Star Schema as a higher level entity. This paper describes MLED_BI and the validation and evaluation approach used.

Implementation of Sales Executive Dashboard for A Multistore Company in Yogyakarta

Information Technology is a part of strategic part for enterprise strategic planning. Information Technology can help the enterprise to determine its strategic planning. Through data from the past, thecompany can learn something and help to decide some strategic issue. A Multistore Company in Yogyakarta has more than five stores. The problem raises to generate real-time sales reporting. Sales manager and owner do not have access to real-time sales condition. To ease management analyzing and reporting sales condition, dimension model of the sales data needs to be built. This dimension model will help to make executive report from some dimensions mentioned in data warehouse. Sales data will pass through some processes: Extract, Transform, and Load (ETL) in order to prepare the data warehouse. This process is preprocessing data before dimensional model is built. In this research multi-dimensional modelling by taking data from 3 stores ranging from 1 February 2014 to 31 January 2015. By implementing sales executive dashboard, it helps to monitor and analyze sales condition. Dashboard shows graphic which ease user, especially sales manager and owner to learn current and updated sales condition based on dimensions: time, outlet / store, and product. Report gives detail information and multidimensionalhelps to analyze data from different perspective.
 Index Terms—Dashboard, Multi Dimentional Model, ETL, Executive Reporting
 REFERENCES[1] W. Eckerson, Performance Dashboard: Measuring,Monitoring, and Managing Your Business, New Jersey: JohnWiley & Sons, 2011.
 [2] O. Romero and A. Abello, "A Survey of MultidimensionalModelling Methodologies," International Journal of Data Warehousing and Mining, vol. 5, no. 2, pp. 1-23, 2009.
 [3] R. Kimball and J. Caserta, The Data Warehouse ETL Toolkit:Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data, Indianapolis: Wiley Publishing, Inc., 2004.
 [4] G. Dhillon and J. Backhouse, "Information System Security Management in the New Millenium," Communications of the ACM, vol. 43, no. 7, pp. 125-128, 2000.
 [5] C. Ballard, D. M. Farrell, A. Gupta, C. Mazuela and S. Vohnik, Dimensional Modelling: In a Business Intelligence Environment, IBM Redbooks, 2006.
 [6] E. Fernández-Medina, J. Trujillo and M. Piattini, "Modeldriven multidimensional modeling of secure datawarehouses," European Journal of Information Systems, vol. 16, no. 4, pp. 374-389, 2007.
 [7] E. Johnson and J. Jones, Building ETL Processes for Business Intelligence Solutions Built on Microsoft SQL Server, CA ERwin, 2007.
 [8] J. Mylopoulos, L. Liu and M. T. Owen, "Database Design," inEnsyclopedia of Database System, United States, Springer,2009, pp. 708 - 710.
 [9] K. R. Gadda and S. Dey, "Business Intelligence for PublicSector Banks in India: A Case study. Design, Development,and Deployment," Journal of Finance, Accounting and Management, vol. 5, no. 2, pp. 37-58, 2014.
 [10] D. J. Power, "DSS Resources," 6 June 2007. [Online]. Available: http://dssresources.com/. [Accessed 29 May 2017].
 [11] D. Hedgebeth, "Data-driven decision making for the enterprise: an overview of business intelligence applications," The Journal of Information and Knowledge Management System, vol. 37, no. 4, pp. 414-420, 2007.
 [12] S. Williams and N. Williams, The Profit Impact of Business Intelligence, San Fransisco: Elsevier, 2007.
 [13] Imelda, "Business Intelligence," in Majalah Ilmiah Unikom, Bandung, UNIKOM, 2013, pp. 111-112.

Implementing a Business Intelligence Environment in Local Market of Pakistan

The BI (Business Intelligence) has gained great success during the last decade throughout the world to aid in decision support with the availability of necessary knowledge to reduce costs, increase revenues and minimize risks. The local market of Pakistan is still not very much aware of its benefits, except some multinationals which are using these tools since almost 7-8 years and earning more revenues and improved performances and a few others are under the process of implementation. The small and medium sized businesses of our local market are focused for the implementation of BI. The pros and cons are identified by analysing the BI tools being used by other large companies here in Pakistan and feasibility of these tools at small and medium enterprises is discussed so that they too may focus on their KPIs (Key Performance Indicator) to increase their performance level.

Measuring the success of changes to Business Intelligence solutions to improve Business Intelligence reporting

Evaluating the success of changes to an existing Business Intelligence (BI) environment means that there is a need to compare the level of user satisfaction with the original and amended versions of the application. The focus of this paper is on producing an evaluation tool, which can be used to measure the success of changes to existing BI solutions to support improved BI reporting. The paper identifies the users involved in the BI process and investigates what is meant by satisfaction in this context from both a user and a technical perspective. The factors to be used to measure satisfaction and appropriate clusters of measurements are identified and an evaluation tool to be used by relevant stakeholders to measure success is developed. The approach used to validate the evaluation tool is discussed and the conclusion gives suggestions for further development and extension of the tool.

BI4BI: A continuous evaluation system for Business Intelligence systems

Business Intelligence (BI) allows supporting decision making by providing methods and tools to easily access and manage business information. Indeed, it is crucial to maintain BI systems and make them evolve in order to fit business and users’ needs. For this purpose, applying BI for BI is suggested. It helps to analyze the current BI environment and to make decisions about its use and evolution. Then, the main contribution of this paper consists in developing a novel system called BI4BI which is based on both BI systems’ data and BI users’ feedbacks.As a result, based on a user centered approach, an automated system for BI evaluation is developed helping its continuous evolution. To this end, system-based and user-based solutions provide two complementary data sources, required to effectively gather insights on the use of BI systems and the way they should evolve. A case study in a semiconductor manufacturer company demonstrates the impact of our solution on the evaluation and evolution of BI systems. Hence, thanks to the involvement of the company’s BI users during the solution design, a set of evaluation criteria responding to their objectives for evaluating the BI system are identified and validated. Furthermore, the results of this case study show that our proposed solution is better than existing ones, in terms of level of focus of its BI evaluation criteria, its level of automation, and its continuous processing.

Depicting Data Quality Issues in Business Intelligence Environment through a Metadata Framework

Modern business intelligence systems depend highly on high quality data. The core of data quality management is to identify all possible sources of data quality problems. To achieve this goal, an extensive metadata infrastructure is the most promising solution. Through theoretical metadata model investigation, the authors identified a set of data quality dimensions by carefully examining the data quality management principles and applied those principles to current BI environment. They summarize their analysis by proposing a BI data quality framework.

Intellectual Provision of the Innovative Entrepreneurship Development

A particular relevance of intellectualization of entrepreneurship is proved in the article. It is offered the concept of securing for entrepreneurship. The intellectual securing provides the organization and self-organization of continuous information and knowledge torrents in the system education-science-entrepreneurship. Intellectual entrepreneurship is considered as the result of the integration of science and entrepreneurship and the channel of transfer's knowledge between them. The authors have proved that the education system should be a key integrator of intelligent and innovative securing of economic subjects. The results of more than a decade experience of formation the professionally significant personal qualities for an entrepreneur are discussed by authors. It is compared and justified the pedagogical approaches, methods and didactic means (with an actualization of attention to the training technology –a fragment of the training is presented, directed to a creative solution of a real situation) of personal qualities' formation, allowing to enter to the business intellectual field. The main results of conducted investigation were: the creation of a complex intellectual supporting of innovative entrepreneurship's development within the educational courses at the university; development of didactic means allowing to identify necessary qualities of the entrepreneur in a business intelligence environment; creating and testing an optimal model of course allowing to prepare an intellectual entrepreneur. DOI: 10.5901/mjss.2015.v6n5s3p303

An IoT Knowledge Reengineering Framework for Semantic Knowledge Analytics for BI-Services

In a progressive business intelligence (BI) environment, IoT knowledge analytics are becoming an increasingly challenging problem because of rapid changes of knowledge context scenarios along with increasing data production scales with business requirements that ultimately transform a working knowledge base into a superseded state. Such a superseded knowledge base lacks adequate knowledge context scenarios, and the semantics, rules, frames, and ontology contents may not meet the latest requirements of contemporary BI-services. Thus, reengineering a superseded knowledge base into a renovated knowledge base system can yield greater business value and is more cost effective and feasible than standardising a new system for the same purpose. Thus, in this work, we propose an IoT knowledge reengineering framework (IKR framework) for implementation in a neurofuzzy system to build, organise, and reuse knowledge to provide BI-services to the things (man, machines, places, and processes) involved in business through the network of IoT objects. The analysis and discussion show that the IKR framework can be well suited to creating improved anticipation in IoT-driven BI-applications.

Decision Model for Software Architectural Tactics Selection Based on Quality Attributes Requirements

Abstract Due to increasing industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture and implementation mechanisms become an important activity. The decisions made during architecture design have significant implications on quality goals. As addressed, there is a lack of available standard models, architectures or frameworks for enabling implementation of quality attributes specially for business intelligence environment and applications in order to rapidly and efficiently supports decision-making. In addition, a lack of researches related to Quality Attributes (QA) requirements, its implementation tactics, and interrelations or correlations between them. The increasing systems complexity mandates software architects to choose from a growing number of design options (decisions) when searching for an optimal architecture design in a specific domain with respect to a defined (set of) quality attributes and constraints. This results in a design space search that is over human capabilities and makes the architectural design task more complicated. In this paper, researcher aimed to reveal most of quality attributes implementation tactics affecting applications architectures, properties. Several quality attributes of software investigated using applied research methods with mixed quantitative (linear) and non-linear analysis techniques. It proposes an initiative for finding an easy and systematic way of addressing quality attributes requirements to a set of implementing architectural tactics. Finally, the findings analyzed and visualized in a way that can support decision stakeholders in addition to a new concept of “safe-tactics” introduced as reduced (pruned) set of tactics that are claimed to be better used in general refactoring cases. In addition, a software tool is developed throughout this research effort as result of gained knowledge and addressing the research findings.

A survey on recent research in business intelligence

Purpose – Business intelligence (BI) has been applied in various domains to take better decisions and it provides different level of information to its stakeholders according to the information needs. The purpose of this paper is to present a literature review on recent works in BI. The two principal aims in this survey are to identify areas lacking in recent research, thereby offering potential opportunities for investigation. Design/methodology/approach – To simplify the study on BI literature, it is segregated into seven categories according to the usage. Each category of work is analyzed using parameters such as purpose, domain, problem identified, solution applied, benefit and outcome. Findings – The BI contribution in various domains, ongoing research in BI, the convergence of BI domains, problems and solutions, results of congregated domains, core problems and key solutions. It also outlines BI and its components composition, widely applied BI solutions such as algorithm-based, architecture-based and model-based solutions. Finally, it discusses BI implementation issues and outlines the security and privacy policies adopted in BI environment. Research limitations/implications – In this survey BI has been discussed in theoretical perspective whereas practical contribution has been given less attention. Originality/value – A comprehensive survey on BI which identifies areas lacking in recent research and providing potential opportunities for investigation.

Investment planning in the petroleum downstream infrastructure

AbstractThe Brazilian oil industry has gained new momentum after the discovery of large oil reserves in deep under‐water. Numerous investments in the oil production chain are expected to support the scale of this operation. Given this context, the use of a decision support system (DSS), which encompasses the complexity of the oil supply chain to support investment decisions, becomes crucial. This paper proposes a DSS that is based on a mixed‐integer linear programming (MILP) model that allows the evaluation of different investment alternatives in logistics networks, such as expanding the capacity for transport, handling, and/or storage. Additionally, the DSS is composed of a database structure, business intelligence environment, and graphical visualization tool. The features of the proposed system were evaluated in two case studies. The first case study assesses the synergies between two projects: specifically the expansion of the berthing capacity of vessels in a marine terminal, and the increase in the transport capacity of the pipeline that connects the marine terminal to a distribution base. The second case study evaluates the dependency of the investment in sections of a pipeline that connects a refinery to several distribution bases. These case studies demonstrate the potential use of a DSS that currently optimizes investments in the Brazilian petroleum supply chain.

Business Intelligence–Hybrid Metaheuristics Techniques

Business Intelligence (BI) is about getting the right information, to the right decision makers, at the right time. A business intelligence environment offers decision makers information and knowledge derived from data processing, through the application of mathematical models and algorithms. BI systems tend to promote a scientific and rational approach to managing enterprises and complex organizations. Soft computing is a collection of new techniques in artificial intelligence, which exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The purpose of this article is to provide an overview of soft computing techniques for the optimal and dynamic decision making system in the current business world.

AN EMPIRICAL ANALYSIS ON BUSINESS INTELLIGENCE MATURITY IN MALAYSIAN ORGANIZATIONS

One of the greatest challenges organizations face today is the lack of infrastructure management. With the increased complexity and information overload, it is difficult for organizations to make quick and informed decisions at the pace required by today’s rapidly changing market. Business intelligence (BI) represents a significant opportunity to improve decision making by providing right information in a timely manner at the right place for the right people. Doing this requires the right management of infrastructure (e.g., people, processes, functionalities) to ensure that the BI environment meets the business expectations and lift BI capabilities to higher level. This researchin-progress paper focuses on an empirical analysis of a proposed BI maturity model among Malaysian organizations. This maturity model comprises of four dimensions: organizational, process, technology, and outcome, spanning across five levels of maturity. An empirical study was undertaken with the development of a structured questionnaire to examine the efficiency of each dimension of BI maturity. Study results show that outcome and organizational dimensions have a higher impact on the BI maturity level of Malaysian organizations. Results also indicate that none of the organizations in Malaysia have achieved level 5 and most of them are still at low level of maturity across all the four dimensions that built into the BI maturity model. Through the understanding of dimensions that affect current level of BI maturity, effective BI roadmaps can be formulated to assist the organizations to make necessary improvement in BI capabilities and keep them productively engaged for a long-term in achieving sustained high performance.

DEVELOPMENTS IN BUSINESS INTELLIGENCE SOFTWARE

In today’s economy the requirements in Business Intelligence environments are changing dramatically. This research paper tested underlying constructs. Hypothesis one sought to test if vendors seek to provide complete BI solutions following all four stages of the CI cycle. The evaluation of BI vendors indicates that all vendors examined do not support planning & directing phase, except for Astragy that gives users consultations to plan and arrange their CI, its absence did not influence the overall performance score. The second hypothesis sought to test if BI vendors fail to provide good enough solutions for the analysis part of the intelligence cycle. The research findings indicate that only two BI vendors, SAS and QlikView, delivering the analysis phase of the intelligence cycle in a proper way. The third hypothetical construct concerns BI vendors’ attempts at making considerable changes in software each year, with each new upgrade. By tracing and comparing the developments of the vendors selected it has been concluded that all BI vendors, irrespective of whether it is a leading traditional vendor or small innovative BI, follow the same tendency in introducing BI enhancements by striving to make its software cost-effective, simpler, faster and flexible for use, scalable to manage increasing amounts of data in businesses, accessible to employees at all levels of organization. Hypothesis four sought to find out if the BI vendors’ software tested can be divided into a number of meaningful subgroups. With reference to evaluation and analysis and empirical findings, it has been concluded that the BI vendors can be divided into sub groups and hence has been classified based on their support of the phases of the intelligence cycle, their developments and market information. The subgroups range from advanced, competent, partially competent, and inadequate to absolutely inadequate. Among the BI vendors assessed, none satisfied the criteria in the advanced category. Hypothesis five aspired to determine if the BI software evaluated should fall under a different term as some of them do not follow the entire BI cycle. The analysis of empirical findings identified that QlikView and TIBCO Spotfire deliver the so-called next generation in-memory analytics, which is faster, much simpler, more flexible and scalable and meet the present-day business needs to a far greater extent if compared to traditional BI.

Conceptual and Theoretical Foundations of Business Intelligence

A B ST R A C T Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers. The objective is to improve the timeliness and quality of inputs to the decision process. Business Intelligence is used to understand the capabilities available in the firm; the state of the art, trends, and future directions in the markets, the technologies, and the regulatory environment in which the firm competes; and the actions of competitors and the implications of these actions. The emergence of the data warehouse as a repository, advances in data cleansing, increased capabilities of hardware and software, and the emergence of the web architecture all combine to create a richer business intelligence environment than was available previously. Although business intelligence systems are widely used in industry, research about them is limited. This paper, in addition to being a tutorial, proposes a BI framework and potential research topics. The framework highlights the importance of unstructured data and discusses the need to develop BI tools for its acquisition, integration, cleanup, search, analysis, and delivery. In addition, this paper explores a matrix for BI data types (structured vs. unstructured) and data sources (internal and external) to guide research.

Operating room data management: improving efficiency and safety in a surgical block

BackgroundEuropean Healthcare Systems are facing a difficult period characterized by increasing costs and spending cuts due to economic problems. There is the urgent need for new tools which sustain Hospitals decision makers work. This project aimed to develop a data recording system of the surgical process of every patient within the operating theatre. The primary goal was to create a practical and easy data processing tool to give hospital managers, anesthesiologists and surgeons the information basis to increase operating theaters efficiency and patient safety.MethodsThe developed data analysis tool is embedded in an Oracle Business Intelligence Environment, which processes data to simple and understandable performance tachometers and tables. The underlying data analysis is based on scientific literature and the projects teams experience with tracked data. The system login is layered and different users have access to different data outputs depending on their professional needs. The system is divided in the tree profile types Manager, Anesthesiologist and Surgeon. Every profile includes subcategories where operators can access more detailed data analyses. The first data output screen shows general information and guides the user towards more detailed data analysis. The data recording system enabled the registration of 14.675 surgical operations performed from 2009 to 2011.ResultsRaw utilization increased from 44% in 2009 to 52% in 2011. The number of high complexity surgical procedures (≥120 minutes) has increased in certain units while decreased in others. The number of unscheduled procedures performed has been reduced (from 25% in 2009 to 14% in 2011) while maintaining the same percentage of surgical procedures. The number of overtime events decreased in 2010 (23%) and in 2011 (21%) compared to 2009 (28%) and the delays expressed in minutes are almost the same (mean 78 min). The direct link found between the complexity of surgical procedures, the number of unscheduled procedures and overtime show a positive impact of the project on OR management. Despite a consistency in the complexity of procedures (19% in 2009 and 21% in 2011), surgical groups have been successful in reducing the number of unscheduled procedures (from 25% in 2009 to 14% in 2011) and overtime (from 28% in 2009 to 21% in 2011).ConclusionsThe developed project gives healthcare managers, anesthesiologists and surgeons useful information to increase surgical theaters efficiency and patient safety. In difficult economic times is possible to develop something that is of some value to the patient and healthcare system too.