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Business Data Strategy

Business Data Strategy
type: Vorlesung (V)
semester: WS 18/19
time: 2018-12-04
09:00 - 17:00 täglich
Geb. 10.50, Raum 604



2019-01-14
09:00 - 17:00 täglich
01.93 Seminarraum K1
01.93 Kronenstraße 32

2019-01-15
09:00 - 17:00 täglich
01.93 Seminarraum K1
01.93 Kronenstraße 32


lecturer: Prof. Dr. Christof Weinhardt
sws: 2
lv-no.: <a target="lvn" href="https://campus.studium.kit.edu/events/J-Br2F35R8aYgEbrshWhdg">2540484</a>
Bibliography
  • Fleckenstein & Fellows (2017) – Modern Data Strategy
  • Leimeister (2015) – Einführung in die Wirtschaftsinformatik
  • Urbach & Ahlemann (2016) – IT-Management im Zeitalter der Digitalisierung
  • DAMA International (2009) – The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK)
Content of teaching

With new methods for capturing and using different types of data and industry’s recognition that society’s use of data is less than optimal, the need for comprehensive strategies is more important than ever before. Advances in cybersecurity and information sharing and the use of data in its raw form for decision making all add to the complexity of integrated processes, ownership, stewardship, and sharing. The life cycle of data in its entirety spans the infrastructure, system design, development, integration, and implementation of information-enabling solutions. This lecture focuses on teaching about these dynamics and tools to comprehend and manage them in organisation contexts. Given the increasing size and complexity of data, methods for the transformation and structured preparation are an important tool in the process of sense–making. Modern software solutions and programming languages provide frameworks for such tasks that form another part of this course ranging from conceptual systems modelling to data manipulation to automated generation of HTML reports and web-applications.

Entryrequirements

Attendance will be limited to 20-30 participants.

Shortdescription

The lecture "Business Data Strategy" focusses on the dynamic interplay of complex streams of data in organisations, specifically how these can be harnessed to create economic value.

Target audience

Students should be familiar with basic concepts of business organizations, information systems, and programming. However, all material will be introduced, so no formal pre-conditions are applied.

Aim
  • Digitalization: Drivers and dynamics
  • Identification of the strategic potentials of intensified data use in organization units and networks
  • Requirements of organizational data management
  • Key performance indicators and monitoring
  • Software based modeling and processing of data streams and automated reporting