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Business Information Systems and Architecture (BISA) Laboratory

Open Data Cases

In recent years, more and more data is open to the Internet. Currently, however, this valuable amount of information from companies remains largely unused. To fill this gap, we develop the Data App Store, an online platform that supports companies in the discovery, integration and use of open data.

• perform a case study on the use of open data in one of the partner companies of the Data App Store project, named NestlГ©, Swisscom and SBB.

Requirements and notation for information supply chains

The concept of information supply consists of all activities and works associated with the conversion of raw data to the delivery of information products to the end consumers and involves the involvement of several actors. It acts as analogy of the product supply chain. The goal is to understand how data circulates in different corporate systems and functions.

• Check the existing literature on the subject
• Determine requests for information supply chains
• suggestions of a notation scheme

• Otto, B., & Ofner, M. (2010). Towards a process reference model for the management of information Supply Chain Management. ECIS.
• Sun, S., & Yen, J. (2005). Information Supply Chain: A uniform framework for information sharing. ISI.

a data management perspective on information safety frames

Information security is covered by various general purpose frames (including governance and auditing, among others). Data management is a subset of these issues falling under the roof of these frameworks and can be addressed either explicitly or implicitly.

• identify security-relevant data management design areas (eg access rights, privacy compliance)
• Select information and check Safety Framework
• providing an assignment of data management design areas and information security requirements

• National Institute for Standards and Technology (NIST), & United States of America. (2014). Framework for improving critical infrastructure Cybersecurity.
• De Haes, S., Van Grembergen, W., & Debreceny, R.S. (2013). COBIT 5 and enterprise governance of information technology: building blocks and research possibilities. Journal of Information Systems, 27 (1), .

Approaches for Big Data Management

Big Data is a relatively new technological trend - so the way you are to be used should be used in corporate environments, still another definition. Big Data Management is the organization, administration and governance of large quantities of structured and unstructured data.

• Review Big Data Data Related Litzature
• identify construction areas and requirements for big data management
• proposes a batch for Big Data Management in Corporate Environments

• Chen, J., Chen, Y., Du, X., Li, C., Lu, J., Zhao, S., & Zhou, X. (2013). Big Data Challenge: A Data Management Perspective. Limits of computer science, 7, .
• Cohen, E., Hirama, K., & Rossi, R. (2015). Mark Big Data Management.

Analytics as Service: Self-Service Analytics

Analytical solutions are mainly adopted by large companies, but the cloud services offer a cost-effective approach to supporting its adoption by a broader assortment of organizations. In fact, the Global Analytics is expected to grow as a service market (AAAs) in 2015 from $ 5.9 billion to $ 22.24 billion in 2020 (ResearchNmartments, 2016). In addition to the reduced cost of implementation, several other factors prefer of cloud services for business analyzes, especially increased mobility due to the scalability of the cloud.

• Review of Literature on Cloud Analytics to examine the various functions that describe AAAs.
• Review of case studies on self-service analysis and their acceptance in organizations.
• analysis requirements for self-service analysis for well-targeted offers

• Baars, H., Kemper, H.-G., 2010. Business Intelligence in the Cloud? In pacis , pp. 145.
• Demirkan, H., Delen, D., 2013. Use the capabilities of the service-oriented decision-making auxiliary systems: Analytics and Big Data in Cloud. Dezis. Support Syst. 55, .
• Ereth, J. and Baare, H.Cloud-based Business Intelligence and Analytics applications - business value and feasibility. In Pacis 2015 procedure . 2015.
• Sun, X., Gao, B., Fan, L., A, W., 2012. A cost-effective approach to the delivery of analyzes as a service, in: 2012 IEEE 19. International Web Services Conference (ICWS). PP. .

User Preferential Models for Cloud Services

By 2020 will be affected "more than 1 trillion US dollar in IT editions directly or indirectly from switching to cloud" (Gartner, 2016). Cloud services are delivered mainly in three basic service models, including infrastructure as a service (IAAS), platform as a service (PAAs) and software as a service (SaaS). Given the quick increase in cloud service offerings, users are confronted with multiple options. You find it difficult to evaluate cloud services with the different power levels and different economic models.

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