Process mining: a framework proposal for pervasive business intelligence

In recent years, global growth slowed, the markets have matured and become more competitive. The impact of computing in organizations made information technology a strategic element to the acquisition and maintenance of competitive advantage. Based on the literature review in the related areas of Business Intelligence (BI) and Process Mining (PM), is presented a framework for improving the decision-making processes in organizations

Business Intelligence Capabilities as Facilitators to Achieve Organizational Agility

Today’s business environment is characterized by fast and unexpected changes, many of which are driven by technological advancement. In such environment, the ability to respond effectively and adapt to the new requirements is not only desirable but essential to survive. Comprehensive and quick understanding of intricacies of market changes facilitates firm’s faster and better response. Two concepts contribute to the success of this scenario; organizational agility and business intelligence (BI). As of today, despite BI’s capabilities to foster organizational agility and consequently improve organizational performance, a clear link between BI and organizational agility has not been established. In this paper we argue that BI solutions have the potential to be facilitators for achieving agility. We aim at showing how BI capabilities can help achieve agility at operational, portfolio, and strategic levels

Applicability of Business Intelligence in Electronic Health Record

AbstractClinical datasets provide an excellent environment in which combined analyses of both structured and unstructured datasets can prove fruitful and useful. With an increasing need to deploy Electronic Health Record (EHR) and Electronic Medical Record (EMR), there is also a corresponding need to apply data mining technologies to extract quality data and inference rules from the information stored in those electronic records so as to provide real-time decision supports and evidence-based practice to clinicians and healthcare providers. Business Intelligence (BI) has emerged as a technology that has the potential to operationalize the repository content of EHR in supporting evidence-based practice and improving the quality of healthcare delivery. In this paper, a literature review was used to explore the key benefits, challenges, and obstacles of incorporating the BI technology into EHR so as to improve the quality and safety of healthcare delivery

Exploring data analytics of data variety

The Internet allows organizations managers access to large amounts of data, and this data are presented in different formats, i.e., data variety, namely structured, semi-structured and unstructured. Based on the Internet, this data variety is partly derived from social networks, but not only, machines are also capable of sharing information among themselves, or even machines with people. The objective of this paper is to understand how to retrieve information from data analysis with data variety. An experiment was carried out, based on a dataset with two distinct data types, images and comments on cars. Techniques of data analysis were used, namely Natural Language Processing to identify patterns, and Sentimental and Emotional Analysis. The image recognition technique was used to associate a car model with a category. Next, OLAP cubes and their visualization through dashboards were created. This paper concludes that it is possible to extract a set of relevant information, namely identifying which cars people like more/less, among other information.COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/201

Big data educational portal for Small and Medium Sized Enterprises (SMEs)

Big Data refers to the massive amount of data generated from IT systems, sensors, and mobile devices. The values of big data are achieved by descriptive, predictive and prescriptive analytics. Small and Medium Sized Enterprises (SMEs) play a significant role in contributing to economic development. Big data is seen as a strategic and innovative tool for SMEs to stay competitive in the marketplace. However, there is lack of research in studying the value of big data to SMEs. Moreover, due to the shortage of quality learning platforms, SMEs have limited understanding of the potential benefits big data offers their businesses. This research aims to propose an educational portal of big data for SMEs by incorporating the pedagogy aspects. The research is underpinned by design science research. The portal contributes theoretically and methodologically by deriving the design knowledge of such portal and practically by increasing big data knowledge among SMEs

Service-Oriented Cognitive Analytics for Smart Service Systems: A Research Agenda

The development of analytical solutions for smart services systems relies on data. Typically, this data is distributed across various entities of the system. Cognitive learning allows to find patterns and to make predictions across these distributed data sources, yet its potential is not fully explored. Challenges that impede a cross-entity data analysis concern organizational challenges (e.g., confidentiality), algorithmic challenges (e.g., robustness) as well as technical challenges (e.g., data processing). So far, there is no comprehensive approach to build cognitive analytics solutions, if data is distributed across different entities of a smart service system. This work proposes a research agenda for the development of a service-oriented cognitive analytics framework. The analytics framework uses a centralized cognitive aggregation model to combine predictions being made by each entity of the service system. Based on this research agenda, we plan to develop and evaluate the cognitive analytics framework in future research

The Effect of Business Intelligence on Management Accounting Information System

In today's business world, we are faced with high volumes of data. New developments in IT provide organizations with effective and efficient access and storage of information. In any case, there is a long distance between the mass of data and its use. Management accounting information system has changed as a key to success in today's business environment. In the field of management accounting, if the accounting information system is not capable of providing information to business managers timely and quickly, organizations' success will be threatened in the competitive environment. To cope with competitors and growth of long-term strategies, the accounting information system should benefit from business intelligence techniques to provide timely and effective financial information. The important competitive advantage against opponents and business competitors in the market is the most important reason to create intelligent systems. The purpose of business intelligence is to help control the flow and resources of business information within and around the organization. In this study, based on the research objectives, using a meta-analysis, some of the applied criteria and parameters of accounting information systems were examined based on business intelligence features. In addition, a model was proposed based on four categories of relationships and inferences, warning and reporting systems, and tools for effective analysis and decision-making. Among the criteria in the literature review are group decision-making, optimization, integration, simulation, traffic reports, prototyping based on the original version, two-way argument process, awareness technology, informing on the content, fuzzificatio, data mining, data storage, real-time analysis process, establishing communication  channels, creating intelligent factors etc. Therefore, the necessity to use a business intelligence-based model in management accounting information system is proposed

Ubiquitous Computing – an Application Domain for Business Intelligence in the Cloud?

A number of IT providers have introduced web-based services for management support that are discussed under the label“Business Intelligence (BI) in the Cloud”. It has been argued that these Cloud products might become valuable complementsto on-premise enterprise BI infrastructures by allowing a flexible addition of sizeable components, tools or – in selected areas– complete solutions. In this publication, it is discussed in how far a Ubiquitous Computing setting based on technologies likeradio frequency identification (RFID) or sensor technology could become a relevant application domain for Cloud-BI”. Themain insights come from a literature review, a series of expert interviews on BI and Cloud Computing, and a case on spareparts logistics. The results indicate that the addressed domain indeed comes with business potential and highlight the need forfurther design oriented research

DECISION SUPPORT WITHIN KNOWLEDGE-BASED ENGINEERING – A BUSINESS INTELLIGENCE-BASED CONCEPT

Essential characteristics of products are set during early phases of product development as well as manufacturing. During these processes, decisions are made without awareness of their final impacts on long term key success factors. Industrial businesses lack concepts that enable decision-makers within knowledge based engineering processes, to anticipate possible impacts of their decisions. Due to this, many industrial companies employ so called knowledge engineers to manually gather and analyze information of product lifecycles. In order to improve the decision support within knowledge based engineering, a concept was developed, which contains the extension of business intelligence environments with product-orientated data warehouses. It is thus possible to combine technical information of product features with the traditional dimensions of managerial analysis in order to identify impacts of decisions on the product lifecycle and hence support knowledge engineers in their daily work

Index based triangulation method for efficient generation of large three-dimensional ultrasonic C-scans

The demand for high speed ultrasonic scanning of large and complex components is driven by a desire to reduce production bottlenecks during the non-destructive evaluation of critical parts. Emerging systems (including robotic inspection) allow the collection of large data volumes in short time spans, compared to existing inspection systems. To maximize throughput, it is crucial that the reconstructed inspection data sets are generated and evaluated rapidly without a loss of detail. This requires new data visualization and analysis tools capable of mapping complex geometries whilst guaranteeing full part coverage. This paper presents an entirely new approach for the visualization of three-dimensional ultrasonic C-scans, suitable for application to high data throughput ultrasonic phased array inspection of large and complex parts. Existing reconstruction approaches are discussed and compared with the new Index Based Triangulation (IBT) method presented. The IBT method produces 3D C-scan representation, presented as coloured tessellated surfaces, and the approach is shown to work efficiently even on challenging geometry. An additional differentiating characteristic of the IBT method is that it allows easy detection of lack of coverage (an essential feature to ensure that inspection coverage can be guaranteed on critical components). Results demonstrate that the IBT C-scan generation approach runs over 60 times faster than a C-scan display based on Delaunay triangulation and over 500 times faster than surface reconstruction C-scans. In summary the main benefits of the new IBT technique are: • High speed generation of C-scans on large ultrasonic data sets (orders of magnitude improvement over surface reconstruction C-Scans) • Ability to operate efficiently on 3D mapped data sets (allowing 3D interpretation of C scans on complex geometry components) • Intrinsic indication of lack of inspection coverag