Transactional Information Systems Research Articles

Применение методов парного сравнения количественных и бинарных выборок в биомедицинских исследованиях с целью принятия управленческих решений

Solving research problems within the framework of creating a single digital circuit in healthcare requires 
 a research conducted on the basis of depersonalized medical data stored in the information systems of medical institutions. There are described the methods of mathematical statistics aimed at comparing the average values of two types of samples: quantitative and binary in order to determine the relationship between blood test indicators and working conditions. Comparison of methods and results of comparison of quantitative and binary samples is made. The expediency of processing small structured samples taken out from the medical information system is substantiated. The study was conducted by using medical data stored in a transactional medical information system. During the preparation process, the data were depersonalized, cleaned from the inevitable noise and defects. Binarization of the values 
 of the indicators was performed by comparing them with the known boundaries of the interval of the medical norm. 
 A method was developed to bring the samples to uniformity simultaneously on the gender and age signs of the patients. There have been revealed the parameters of laboratory tests, which have a statistically significant relationship with working conditions identified for 4 groups under study. These groups were corresponding to the following work conditions complexes: influence of electromagnetic emanation, noise and vibrations, working conditions in regional office services. The proposed methods and received results will increase the accuracy of the performed risk assessments of occupational morbidity and become the base for studying the mechanism of the work conditions influencing the health. They will contribute to improvement of the analysis of the data collected in the medical information systems and management decision-making in healthcare.

A multi-perspective approach for the analysis of complex business processes behavior

Business processes are often monitored by transactional information systems that produce massive dataset called event logs. Such logs contain the process execution traces, typically characterized by heterogeneous and high-dimensional data. Process mining techniques offer a great opportunity to gain valuable knowledge hidden in the data to be used for analysing the multiple characteristics of processes (i.e. perspectives in process mining, like structural aspects, activities, resources, data and time). Therefore, raw data must be encoded into a suitable format that can be more conveniently provided to the mining algorithms. However, most of the existing process encoding techniques focus on the control-flow perspective, i.e. only encode the sequence of activities that characterize a trace, leaving out other process perspectives that are fundamental for describing the process behavior in all its aspects. In this paper we address the problem of computing a concise and informative representation of execution traces that considers the multiple perspectives of the process behavior. We propose a holistic approach that computes trace embedding able to capture patterns of dependencies between the perspectives that are lost in a one-dimensional analysis and, at the same time, it is unsupervised, meaning that no a priori knowledge is needed. The experiments conducted on two real life logs demonstrate that our proposed embedding is appropriate to concisely describe the multiple and various characteristics of the processes, and that the proposed method outperforms existing trace encoding techniques. Furthermore, the embedding includes the elapsed time between events as an additional feature to make us capable to use it as a further dimension of analysis.

A model of mining approximate frequent itemsets using rough set theory

Datasets can be described by decision tables. In real-life applications, data are usually incomplete and uncertain, which presents big challenges for mining frequent itemsets in imprecise databases. This paper presents a novel model of mining approximate frequent itemsets using the theory of rough sets. With a transactional information system constructed on the dataset under consideration, a transactional decision table is put forward, then lower and upper approximations of support are available which can be easily computed from the indiscernibility relations. Finally, by a divide-and-conquer way, the approximate frequent itemsets are discovered taking consideration of support-based accuracy and coverage defined. The evaluation of the novel model is conducted on both synthetic datasets and real-life applications. The experimental results demonstrate its usability and validity.

Gaining competitive advantage through business analytics

The industry for business analytics within the BI sphere is growing significantly and the distinction in organizations between transactional information systems and decision-oriented systems breaks down. Firms need to understand both the opportunity and the potential of business analytics. Reporting, which is getting a handle on what happened in organizations, is complemented by analytics that is rather explanatory and predictive. Leveraging business analytics means to use analytics applications in order to analyse business problems and produce related business recommendations to improve business process performance. Business analytics must but be a part of a value creating process operating together with other systems and organisational factors in a synergistic manner, including people, processes, knowledge and relationship assets, culture, structure, and policies. In order for companies to be efficient, they need to automate processes, workflows and make rules. Effectiveness, on the other hand, is about making better decisions, perhaps using the same data that their competitors may have. What matters is not necessarily the technologies deployed, but emerging competence that the firm uses to support its business. A specific “mindset” needs to be installed for companies to invest into business analytics. Organisations need to better understand how best to exploit their data and convert them into information and sense-making capabilities. Business capabilities can be enhanced not only by exploitation of analytical tools, but also by the sophisticated use of information. This leads to a truly sense-making capability or “analytical mindset”. The primary data covers 398 data sets, where firms have been asked about the specifics of their information management. The data is used as input to statistical tests and the value of business analytics is being analyzed in an empirical way.

Methodological guidelines for reducing the complexity of data warehouse development for transactional blood bank systems

Over time, data warehouse (DW) systems have become more difficult to develop because of the growing heterogeneity of data sources. Despite advances in research and technology, DW projects are still too slow for pragmatic results to be generated. Here, we address the following question: how can the complexity of DW development for integration of heterogeneous transactional information systems be reduced? To answer this, we proposed methodological guidelines based on cycles of conceptual modeling and data analysis, to drive construction of a modular DW system. These guidelines were applied to the blood donation domain, successfully reducing the complexity of DW development.

A novel approach for process mining based on event types

Despite the omnipresence of event logs in transactional information systems (cf. WFM, ERP, CRM, SCM, and B2B systems), historic information is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. Given its potential and challenges it is no surprise that recently process mining has become a vivid research area. In this paper, a novel approach for process mining based on two event types, i.e., START and COMPLETE, is proposed. Information about the start and completion of tasks can be used to explicitly detect parallelism. The algorithm presented in this paper overcomes some of the limitations of existing algorithms such as the ?-algorithm (e.g., short-loops) and therefore enhances the applicability of process mining.

Matching observed behavior and modeled behavior: An approach based on Petri nets and integer programming

Inspired by the way SAP R/3 and other transactional information systems log events, we focus on the problem to decide whether a process model and a frequency profile “fit” together. The problem is formulated in terms of Petri nets and an approach based on integer programming is proposed to tackle the problem. The integer program provides necessary conditions and, as shown in this paper, for relevant subclasses these conditions are sufficient. Unlike traditional approaches, the approach allows for labeled Petri nets with “hidden transitions”, noise, etc.

Business alignment: using process mining as a tool for Delta analysis and conformance testing

Increasingly, business processes are being controlled and/or monitored by information systems. As a result, many business processes leave their “footprints” in transactional information systems, i.e., business events are recorded in so-called event logs. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. In this paper we focus on the potential use of process mining for measuring business alignment, i.e., comparing the real behavior of an information system or its users with the intended or expected behavior. We identify two ways to create and/or maintain the fit between business processes and supporting information systems: Delta analysis and conformance testing. Delta analysis compares the discovered model (i.e., an abstraction derived from the actual process) with some predefined processes model (e.g., the workflow model or reference model used to configure the system). Conformance testing attempts to quantify the “fit” between the event log and some predefined processes model. In this paper, we show that Delta analysis and conformance testing can be used to analyze business alignment as long as the actual events are logged and users have some control over the process.

CRM and customer‐centric knowledge management: an empirical research

Current competitive challenges induced by globalization and advances in information technology have forced companies to focus on managing customer relationships, and in particular customer satisfaction, in order to efficiently maximize revenues. This paper reports exploratory research based on a mail survey addressed to the largest 1,000 Greek organizations. The objectives of the research were: to investigate the extent of the usage of customer‐ and market‐related knowledge management (KM) instruments and customer relationship management (CRM) systems by Greek organizations and their relationship with demographic and organizational variables; to investigate whether enterprises systematically carry out customer satisfaction and complaining behavior research; and to examine the impact of the type of the information system used and managers’ attitudes towards customer KM practices. In addition, a conceptual model of CRM development stages is proposed. The findings of the survey show that about half of the organizations of the sample do not adopt any CRM philosophy. The remaining organizations employ instruments to conduct customer satisfaction and other customer‐related research. However, according to the proposed model, they are positioned in the first, the preliminary CRM development stage. The findings also suggest that managers hold positive attitudes towards CRM and that there is no significant relationship between the type of the transactional information system used and the extent to which customer satisfaction research is performed by the organizations. The paper concludes by discussing the survey findings and proposing future research.

Transactional information systems: theory, algorithms, and the practice of concurrency control and recovery

Transactional Information Systems is the long-awaited, comprehensive work from leading scientists in the transaction processing field. Weikum and Vossen begin with a broad look at the role of transactional technology in today's economic and scientific endeavors, then delve into critical issues faced by all practitioners, presenting today's most effective techniques for controlling concurrent access by multiple clients, recovering from system failures, and coordinating distributed transactions. The authors emphasize formal models that are easily applied across fields, that promise to remain valid as current technologies evolve, and that lend themselves to generalization and extension in the development of new classes of network-centric, functionally rich applications. This book's purpose and achievement is the presentation of the foundations of transactional systems as well as the practical aspects of the field what will help you meet today's challenges. * Provides the most advanced coverage of the topic available anywhere--along with the database background required for you to make full use of this material. * Explores transaction processing both generically as a broadly applicable set of information technology practices and specifically as a group of techniques for meeting the goals of your enterprise. * Contains information essential to developers of Web-based e-Commerce functionality--and a wide range of more traditional applications. * Details the algorithms underlying core transaction processing functionality. Table of Contents PART ONE - BACKGROUND AND MOTIVATION Chapter 1 What Is It All About? Chapter 2 Computational Models PART TWO - CONCURRENCY CONTROL Chapter 3 Concurrency Control: Notions of Correctness for the Page Model Chapter 4 Concurrency Control Algorithms Chapter 5 Multiversion Concurrency Control Chapter 6 Concurrency Control on Objects: Notions of Correctness Chapter 7 Concurrency Control Algorithms on Objects Chapter 8 Concurrency Control on Relational Databases Chapter 9 Concurrency Control on Search Structures Chapter 10 Implementation and Pragmatic Issues PART THREE - RECOVERY Chapter 11 Transaction Recovery Chapter 12 Crash Recovery: Notion of Correctness Chapter 13 Page Model Crash Recovery Algorithms Chapter 14 Object Model Crash Recovery Chapter 15 Special Issues of Recovery Chapter 16 Media Recovery Chapter 17 Application Recovery PART FOUR - COORDINATION OF DISTRIBUTED TRANSACTIONS Chapter 18 Distributed Concurrency Control Chapter 19 Distributed Transaction Recovery PART FIVE - APPLICATIONS AND FUTURE PERSPECTIVES Chapter 20 What Is Next?

Transactional information systems

Transactional information systems

The strategic dimension of transactional information systems: some organizational implications

. Often information systems (IS) are classified in three groups: (a) transactional, used mainly for co-ordination and resource allocation purposes at the operational level of a company; (b) tactical, often employed to support the resource procurement activities typical of middle management; and (c) information systems for strategic decision making, designed to help in the planning and strategy design processes which are the direct responsibility of top management. In general, the amount of care and management attention that companies give to these different types of systems is proportional to their position in this hierarchy: little attention is devoted to the mundane transaction-pushing systems and exquisite care is put into developing the sophisticated decision making aid for the CEO and his/her staff. The IS/IT literature has been reporting quite commonly cases in which companies have attained or lost great competitive advantages by way of their transactional information systems [for example, Emery Worldwide, Baxter Healthcare ASAP system, and Frontier Airlines]. The aim of this paper is to identify actions that companies can take to realize potential benefits of their IS, in particular from their low-level, transactional IS. Among other actions, we will conclude that companies would be better off if they: (a) have the IS department at the right place in the organization, staffed with people knowledgeable about the basic nature of the business in which the company is engaged; (b) are sensible to what can be called ‘strategic maintenance’ of systems, (c) set up a formal procedure for IS planning to ensure coherence between IS plans and business plans, derived, in turn, from business strategy, and (d) keep abreast of the relevant technology. Several examples taken from European companies are used to illustrate these conclusions.