How to start with big data - a multiple case study

As part of an advancing digitalization, many enterprises feel the need to explore the possibilities big data may provide for their business. However, only a few companies use big data applications productively, despite its high expected potential. How companies examine the possibilities of big data, is therefore a highly interesting and relevant question. Based on a multiple case study we identify three different approaches: Companies either initially focus entirely on business aspects, or on a systematic build-up of a big data technology and data platform. Innovation adoption research is used as a theoretical basis

Strategies and Influencing Factors for Big Data Exploration

Many enterprises feel the need to explore the possibilities big data may provide for their business. However, they hesitate to apply big data, as they are unsure how to successfully identify new opportunities. We analyze in a multiple case study how companies start to investigate big data applications. Based on these case studies, we find two generic strategies companies tend to follow. These strategies focus either on the search for potential business opportunities or on the need to develop technology infrastructure. In order to understand the strategy selection, we utilize the Technology-Organization-Environment (TOE) framework. Our findings are twofold. First, we identify factors that influence the choice of strategy. Second, we identify the factors that influence the initiation phase of big data adoption within a chosen strategy

Activities to Build a Digital Corporate Culture–A Multiple-case Study on the Prerequisites for Digital Innovation

Digital innovation enables competitive advantage by seizing new digital opportunities. Therefore, it is crucial for organizations to be prepared and aligned to manage digital innovation initiatives. To create the conditions for digital innovation, companies need the capability to develop a digital corporate culture. Recent research has explored this ability in different contexts, but there is little in-depth knowledge on how organizations develop a digital culture. We conducted a multiple-case study focusing on companies’ practices for developing a digital corporate culture and thus creating the prerequisites for digital innovation. We identified six key activities that support the building of digital skills and the development of a suitable organization for digital innovation projects. Furthermore, we provide a comprehensive picture of these key activities that reveals interactions, relationships, and contexts. Our results provide a better understanding of the relationship between the capability to develop a digital culture and digital innovation initiatives in organizations

Exclusive meson production at COMPASS

We explore the feasibility to study exclusive meson production (EMP) in hard muon-proton scattering at the COMPASS experiment. These measurements constrain the off-forward parton distributions (OFPD's) of the proton, which are related to the quark orbital contribution to the proton spin.Comment: Workshop on Exclusive and Semi-Exclusive Processes at High Momentum Transfer, Jefferson Lab, 20-22 Mai 199

CAPTURE AND ANALYSIS OF SENSOR DATA FOR ASTHMA PATIENTS

Worldwide more than 230 million people suffer from asthma. Reliable and timely guidance for indi-viduals to minimize their risk for asthma attacks is not available. This is largely due to the fact that asthma symptoms are often caused by multiple environmental and personal factors. Many of them are neither captured nor systematically analysed. This is addressed by the project ActOnAir. It aims at a comprehensive capture of health factors and the environmental exposure of individuals, as well as a subsequent analysis in real-time. For this purpose the ActOnAir system provides a mobile sensor box for data collection, a sensor data integration and processing platform, a data mining component and a smartphone application for patients. This contribution outlines the design objectives of the ActOnAir system and discusses corresponding key requirements. The related system architecture is introduced and first results from a prototype implementation are sketched

Guided Machine Learning for Business Users

Advanced and predictive analytics are playing an increasingly important role in all industries. However, the productive use of new analytic methods and applications seems to stagnate. One reason for this is a lack of people with the necessary data science skills, especially for small and medium sized businesses. This paper proposes design principles that are important for enhancing the usage and adoption of applications for advanced and predictive analytics. The identified principles are implemented in a prototype application for predictive maintenance which can be used by employees without knowledge of data mining and machine learning

In-Memory Data Management im Einzelhandel: Einsatzbereiche und Nutzenpotentiale

Aktuelle Entwicklungen im Bereich In-Memory Data Management können die Art und Weise, wie betriebliche Anwendungen in Zukunft genutzt werden, signifikant verändern. So ist es möglich, große Volumen von Einzelbelegen direkt in Hauptspeichern vorzuhalten und dort mit hoher Geschwindigkeit zu bearbeiten. Um In-Memory Data Management erfolgreich einzuführen und weiterzuentwickeln, ist es notwendig zu verstehen, welche Arten von Anwendungen von dieser Technologie am meisten profitieren können. Hierzu beschreiben wir mögliche Einsatzbereiche aus dem Einzelhandel. Die Verallgemeinerung von Geschäfts-prozesseigenschaften und Nutzenpotentialen führt zu typischen Anwendungsmustern

A Comparison of Smart City Development and Big Data Analytics Adoption Approaches.

This paper intends to elucidate the similarities between smart city development and big data analytics adoption. Both concepts promise new opportunities: smart cities to improve citizens’ life quality and big data analytics to drive companies towards the competitive edge. Consequently, the number of organisational big data initiatives and efforts to implement smart city concepts are increasing. In the context of big data analytics adoption, it could be shown that there are two distinct approaches companies follow. They either focus on the search for potential use cases or on the development of a technology infrastructure. Based on a comparison of various smart city and big data analytics use cases, this paper discloses that both of these approaches either concentrate on developing new service development or providing the required infrastructures for future services