Parasitic Order Machine. A Sociology and Ontology of Information Securing

This study examines information security as a process (information securing) in terms of what it does, especially beyond its obvious role of protector. It investigates concepts related to ‘ontology of becoming’, and examines what it is that information securing produces. The research is theory driven and draws upon three fields: sociology (especially actor-network theory), philosophy (especially Gilles Deleuze and Félix Guattari’s concept of ‘machine’, ‘territory’ and ‘becoming’, and Michel Serres’s concept of ‘parasite’), and information systems science (the subject of information security). Social engineering (used here in the sense of breaking into systems through non-technical means) and software cracker groups (groups which remove copy protection systems from software) are analysed as examples of breaches of information security. Firstly, the study finds that information securing is always interruptive: every entity (regardless of whether or not it is malicious) that becomes connected to information security is interrupted. Furthermore, every entity changes, becomes different, as it makes a connection with information security (ontology of becoming). Moreover, information security organizes entities into different territories. However, the territories – the insides and outsides of information systems – are ontologically similar; the only difference is in the order of the territories, not in the ontological status of entities that inhabit the territories. In other words, malicious software is ontologically similar to benign software; they both are users in terms of a system. The difference is based on the order of the system and users: who uses the system and what the system is used for. Secondly, the research shows that information security is always external (in the terms of this study it is a ‘parasite’) to the information system that it protects. Information securing creates and maintains order while simultaneously disrupting the existing order of the system that it protects. For example, in terms of software itself, the implementation of a copy protection system is an entirely external addition. In fact, this parasitic addition makes software different. Thus, information security disrupts that which it is supposed to defend from disruption. Finally, it is asserted that, in its interruption, information security is a connector that creates passages; it connects users to systems while also creating its own threats. For example, copy protection systems invite crackers and information security policies entice social engineers to use and exploit information security techniques in a novel manner.

Data Governance and Automated Marketing – A Case Study of Expected Benefits of Organizing Data Governance in an ICT Company

This research is looking to find out what benefits employees expect the organization of data governance gains for an organization and how it benefits implementing automated marketing capabilities. Quality and usability of the data are crucial for organizations to meet various business needs. Organizations have more data and technology available what can be utilized for example in automated marketing. Data governance addresses the organization of decision rights and accountabilities for the management of an organization’s data assets. With automated marketing it is meant sending a right message, to a right person, at a right time, automatically. The research is a single case study conducted in Finnish ICT-company. The case company was starting to organize data governance and implementing automated marketing capabilities at the time of the research. Empirical material is interviews of the employees of the case company. Content analysis is used to interpret the interviews in order to find the answers to the research questions. Theoretical framework of the research is derived from the morphology of data governance. Findings of the research indicate that the employees expect the organization of data governance among others to improve customer experience, to improve sales, to provide abilities to identify individual customer’s life-situation, ensure that the handling of the data is according to the regulations and improve operational efficiency. The organization of data governance is expected to solve problems in customer data quality that are currently hindering implementation of automated marketing capabilities.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Cardiac Imaging in the Diagnosis of Coronary Artery Disease: The Value of Quantitative Imaging of Myocardial Perfusion and Deformation

Atherosclerosis is a chronic and progressive disease of the vasculature. Increasing coronary atherosclerosis can lead to obstructive coronary artery disease (CAD) or myocardial infarction. Computed tomography angiography (CTA) allows noninvasive assessment of coronary anatomy and quantitation of atherosclerotic burden. Myocardial blood flow (MBF) can be accurately measured in absolute terms (mL/g/min) by positron emission tomography (PET) with [15O] H O as a radiotracer. We studied the coronary microvascular dysfunction as a risk factor for future coronary calcification in healthy young men by measuring the coronary flow reserve (CFR) which is the ratio between resting and hyperemic MBF. Impaired vasodilator function was not linked with accelerated atherosclerosis 11 years later. Currently, there is a global interest in quantitative PET perfusion imaging. We established optimal thresholds of [15O] H O PET perfusion for diagnosis of CAD (hyperemic MBF of 2.3 mL/g/min and CFR of 2.5) in the first multicenter study of this type (Turku, Amsterdam and Uppsala). In myocardial bridging a segment of the coronary artery travels inside the myocardium and can be seen as intramural course (CTA) or systolic compression (invasive coronary angiography). Myocardial bridging is frequently linked with proximal atherosclerotic plaques. We used quantitative [15O] H O PET perfusion to evaluate the hemodynamic effects of myocardial bridging. Myocardial bridging was not associated with decreased absolute MBF or increased atherosclerotic burden. Speckle tracking allows quantitative echocardiographic imaging of myocardial deformation. Speckle tracking during dobutamine stress echocardiography was feasible and comparable to subjective wall motion analysis in the diagnosis of CAD. In addition, it correctly risk stratified patients with multivessel disease and extensive ischemia.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Possibilities and challenges in utilization of information provided by Industrial Internet applications

Global digitalization has affected also industrial sector. A trend called Industrial Internet has been present for some years and established relatively steady position in businesses. Industrial Internet is also referred with the terminology Industry 4.0 and in consumer businesses IoT (Internet of Things). Eventually, trend consists of many traditionally proven technologies and concepts, such as condition monitoring, remote services, predictive maintenance and Internet customer portals. All these technologies and information related to them are estimated to change the rules of business in industrial sector. This may result even a new industrial revolution. This research has its focus on Industrial Internet products, services and applications. The study analyses four case companies and their digital service offerings. According to this analysis the comparison of these services is done to find out if there is still space for companies to gain competitive advantage through differentiation with these state of the art solutions. One of the case companies, Case Company Ltd., is working as a primary case company and a subscriber of this particular research. The research and results are analyzed primarily from this company’s perspective and need. In empirical part, the research clarifies how Case Company Ltd. has allocated its development resources through last five years. These allocations in certain categories are then compared to other case companies’ current customer offering and conclusions are made how the approach of different companies differ from each other. Existing theoretical knowledge of Industrial Internet is about to find its shape. In this research we take a look how the case company analysis and findings correlate with the existing knowledge and literature of the topic.