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BIGSALUD (Big Data and Artificial Intelligence for health system optimization) is a project funded by the Valencian Institute for Business Competitiveness (IVACE) and the European Union through the European Regional Development Fund (FEDER). The general objective of the project is to advance in the optimization of disease management through research in software techniques based on Machine Learning with the purpose of helping the clinical staff in the decision-making process, making possible a better diseases diagnosis and prognosis, and a more personalized and effective treatment of patients. This document describes the work that has been carried out for the design and implementation of a prototype for the Big Data Analytics Platform, at the Health line. In a general way, this work has focused on analysis, design and implementation tasks, to cover the specific needs of the Health domain. ; BIGSALUD. Project funded by the Valencian Institute of Business Competitiveness (IVACE) and European Union through the European Regional Development Fund (ERDF), within the public grant program adressed to Technological Institutes of the Valencian Community for the development of non-economic R&D projects carried out in cooperation with companies during 2019 with 151.777,90€. File number: IMDEEA/2019/92

Big data applications combined with analytical tools foster prediction techniques that impact societal, economic, and political changes. After almost a decade of studies, this paper proposes to identify major debates on big data analytics, presenting its evolution over the past years and identifying its research tendencies. We limited our research to the top eight journals in information systems. Our findings suggest that big data analytics is apparently reaching a plateau, which might be confirmed by publications in the following years. The paper contributes to the current debate on big data by identifying ongoing studies in the research community. In addition, it provides a critical analysis of the field development, from its perceived benefits to its unimagined consequences. Finally, we conclude that other perspectives on big data analytics might include a new wave of studies and that new paths beyond productivity gains can be explored.

"This volume explores the diverse applications of advanced tools and technologies of the emerging field of big data and its evidential value in business. It examines the role of analytics tools and methods of using big data in strengthening businesses to meet today's information challenges and shows how businesses can adapt big data for effective businesses practices. Big Data Analytics: Harnessing Data for New Business Models looks at the challenges related to this innovative technology, its diverse applications in the business context, how this technology can enhance the decision-making process, and how it contributes to achieving sustainable development goals. The volume is divided in several areas, focusing on Opportunities and challenges of big data Big data and the business decision-making process Business examples of big data applications: Big data and sustainable development Significant investments have been made in recent years in companies' infrastructure to increase their capacity to collect data. Practically, all aspects of a business are now open to data collection: operations, manufacturing, supply chain management, customer behavior, the performance of marketing campaigns, flow management procedures, etc. At the same time, data about events outside the company, such as market trends, company news, and competitors' activities, is now widely available. This volume shows how big data and the use of data analytics is being effectively adopted more frequently, especially in companies that are looking for new methods to develop smarter capabilities and tackle challenges in dynamic processes. Many illustrative case studies are presented that highlight how companies in every sector are now focusing on harnessing data to create a new way of doing business. This book will familiarize readers with the different concepts related to big data analytics for business applications. It will help readers to enrich their knowledge and gain more insight on how big data and analytics techniques work and how they can take advantage of the opportunity offered by this practical exciting field"--

Regardless of the nature, size, or business sector, organizations are now collecting burgeoning various volumes of data in different formats. As much as voluminous data are necessary for organizations to draw good insights needed for making informed decisions, traditional architectures and existing infrastructures are limited in delivering fast analytical processing needed for these Big Data. For success organizations need to apply technologies and methods that could empower them to cost effectively analyze these Big Data. However, many organizations in developing countries are constrained with limited access to technology, finances, infrastructure and skilled manpower. Yet, for productive use of these technologies and methods needed for Big Data analytics, both the organizations and their workforce need to be prepared. The major objective for this study was to investigate developing countries organizations' readiness for Big Data analytics. Data for the study were collected from a public sector in South Africa and analyzed quantitatively. Results indicated that scalability, ICT infrastructure, top management support, organization size, financial resources, culture, employees' e-skills, organization's customers' and vendors are significant factors for organizations' readiness for Big Data analytics. Likewise strategies, security and competitive pressure were found not to be significant. This study contributes to the scanty literature of Big Data analytics by providing empirical evidence of the factors that need attention when organizations are preparing for Big Data analytics.

Eine Implementierung der Big Data Analytics-Thematik bringt Herausforderungen und Besonderheiten für die pädagogische Praxis mit sich. Hierfür sind nicht nur Aspekte rund um Sensorik, Tracking und Algorithmen relevant; auch ethische Auseinandersetzungen und das Aufzeigen bestehender Wertekonflikte stellen zentrale Punkte dar. Ausgehend von diesen Schwierigkeiten werden Ansätze und Vorschläge vorgestellt, die aus der Perspektive der Medienpädagogik entwickelt wurden.

Abstract
We show how to lawfully buy an election. The key things that make it possible to buy an election are the existence of public voter registration lists and the existence of Big Data Analytics that can predict how a given elector will vote in an election. Someone interested in buying an election can enter an employment contract with some of the opponent electors where these electors are paid to do a job that prevents them from voting. By purchasing access to public voter registration lists, it is possible to verify ex post whether the opponent electors have abstained. In the last two sections, we discuss several barriers that can undermine an attempt to buy an election in the manner we identify.

SAIN4 is a project funded by the Valencian Institute for Business Competitiveness (IVACE) and the European Union through the European Regional Development Fund (FEDER). The purpose of this document is to collect the results of the construction of the Big Data Analytics and Data Capture infrastructure, which will allow the digitization of the production processes and serve the Advanced Management System (AMS) of the data necessary for its operation. ; SAIN4. Project funded by the Valencian Institute of Business Competitiveness (IVACE) and European Union through the European Regional Development Fund (ERDF), within the public grant program adressed to Technological Institutes of the Valencian Community for 2016 with 67.395,60€. File number: IIMDEEA/2017/73