This book constitutes the proceedings of the 6th International Conference on Software and Data Technologies, ICSOFT 2011, held in Seville, Spain, in July 12011. The 13 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 220 submissions. The papers are organized in topical sections on enterprise software technology; software engineering; distributed systems; data management; knowledge-based systems.

This book contains the best papers of the First International Conference on Software and Data Technologies (ICSOFT 2006), organized by the Institute for Systems and Technologies of Information, Communication and Control (INSTICC) in cooperation with the Object Management Group (OMG). Hosted by the School of Business of the Polytechnic Institute of Setubal, the conference was sponsored by Enterprise Ireland and the Polytechnic Institute of Setúbal. The purpose of ICSOFT 2006 was to bring together researchers and practitioners int- ested in information technology and software development. The conference tracks were “Software Engineering”, “Information Systems and Data Management”, “Programming Languages”, “Distributed and Parallel Systems” and “Knowledge Engineering.” Being crucial for the development of information systems, software and data te- nologies encompass a large number of research topics and applications: from imp- mentation-related issues to more abstract theoretical aspects of software engineering; from databases and data-warehouses to management information systems and kno- edge-base systems; next to that, distributed systems, pervasive computing, data quality and other related topics are included in the scope of this conference. ICSOFT included in its program a panel to discuss the future of software devel- ment, composed by six distinguished world-class researchers. Furthermore, the c- ference program was enriched by a tutorial and six keynote lectures. ICSOFT 2006 received 187 paper submissions from 39 countries in all continents.

This book constitutes the refereed proceedings of the 4th International Conference on Software and Data Technologies, ICSOFT 2009, held in Sofia, Bulgaria, in July 2009. The 19 revised full papers presented together with two invited papers were carefully reviewed and selected as best papers from 212 submissions. The papers are organized in topical sections on enterprise software technology; software engineering; distributed systems; data management; knowledge-based systems.

Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education. With a focus on computational tools, the book shows readers how to improve thei

Emerging data technologies are one of several forces that are changing the world. Following a unique macro, meso and micro structure, this textbook shows how technologies such as the Internet of Things, Artificial Intelligence and data analytics are altering business operations and strategy.

This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support of collective computational intelligence such as Web 2.0 social networks, semantic web for data annotation, knowledge representation and inference, data privacy and security, and enabling distributed and collaborative paradigms such as P2P, Grid and Cloud Computing due to the geographically dispersed and distributed nature of the data. The book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generations collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.

This book constitutes the refereed proceedings of the Third EAI International Conference on IoT and Big Data Technologies for Health Care, IotCARE 2022, which took place virtually during December 12-13, 2022. The 23 papers included in this volume were carefully reviewed and selected from 67 submissions. The papers are present newest results in big data technologies for e-health and for e-care. The papers are organized in the following topical sections: big data technologies for e-health; and big data technologies for e-care.

This book presents original research on analytics and context awareness with regard to providing sophisticated learning services for all stakeholders in the eLearning context. It offers essential information on the definition, modeling, development and deployment of services for these stakeholders. Data analysis has long-since been a cornerstone of eLearning, supplying learners, teachers, researchers, managers and policymakers with valuable information on learning activities and design. With the rapid development of Internet technologies and sophisticated online learning environments, increasing volumes and varieties of data are being generated, and data analysis has moved on to more complex analysis techniques, such as educational data mining and learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data in various formats, of tracking user-system and user-user interactions, and of delivering rich contextual information.

Seminar paper from the year 2017 in the subject Computer Science - Software, grade: 1,0, California Lutheran University (Business Administration), course: MBA for Executives, language: English, abstract: In this research paper, the author would like to take a look at the current Big Data vendors, and present the status quo of the leading Big Data solutions. The Big Data market has grown significantly in the last years. The offered solutions are very sophisticated and cover a broad range of user requirements, and have become more user friendly. In the recent years, several well-known IT companies released new products that specialize in Big Data analysis. The desire to analyze more and more data to gain a better understanding of e.g. customer needs, manufacturing efficiencies or e.g. to create predictive analysis based on past consumer behavior drove the need to enhance the functionality of existing business intelligence solutions towards a more open Big Data architecture, that allows the analysis of massive amounts of structured and unstructured data.