Download Zukunftstechnologien

Prof. Ph.D. (CPU) Michael Paetsch
Kolloquium: Dienstag 12.00-13.00
Büro: W1.4.032
Email: [email protected]
Zukunftstechnologien
Syllabus
Sommersemester
2016
Zeit (Raum):
siehe Semesterplaung
Start:
siehe Semesterplanung
SWS:
2 (à 45 Minuten)
ECTS-Credits:
3
Level:
Introduction
Lehrsprache:
Deutsch
Voraussetzungen:
Curiosity
Zugehörige LV’s:
---
Course overview:
We are currently witnessing the development and increasingly widespread introduction of a
large array of technologies that will fundamentally redefine the way companies are interacting
with consumers and – equally important – consumers interact with companies.
A large part of these technologies are in the area of IT and include among others platform’s
and tools to store, manipulate and analyze large amount of data. Increasingly these tasks are
performed autonomous and in real time with systems that are based on Artificial Intelligence
(AI). These systems are predominantly designed to better understand consumer behavior
and profit from these insights, by building better products or services faster and cheaper.
Another set of technologies are developed that will radically improve the information and/or
data exchange between companies and consumers or generate valuable data between
companies and assets. Specifically, these are enabling technologies such as – for example super advanced mobile and connectionless payment systems as well as IOT systems
connected to internet of things (IOT) platforms. The relevance to advancements in sensoring
and biometrics will be discussed.
Finally, key visionary concepts such as Industry 4.0, which could change the production logic
and flow fundamentally - although they are not yet well defined – are presented.
Subsequently,advancements in key non-IT technologies such 3D printing and robotics are
discussed. Other visionary concepts such as self-driving car a and electric cars and smart
grid / smart metering and their underlying technology are outlined.
Key Learnings:
At the outset, the course strives to provide students with a very broad overview of dozens of
emerging technologies. Following, more mature/visible technologies are highlighted and are
discussed in greater conceptual detail.
As indicated above these technologies comprise of – but are not limited to – big
data/business analytics, cloud technologies and player, internet of things platforms, sensoring
and transmission, 5G network developments, contactless/mobile payment systems etc.
After students are familiarized with key technologies shaping todays markets, the primary
focus shifts to understanding how these technologies are fundamentally changing the value
chains and organization of companies and markets.
Specifically, students will also be introduced to the concept of data monetization and
advanced new business models. It will provide a very good overview of how companies other
than google and facebook are generating money with data.
A great deal of effort is spent in making students understand, how these technologies push
universal digitization of all internal and external processes and thereby - as a consequence will massively transform existing industries or create entirely new once.
Course contributions to bachelor programs’ common learning goals:
Learning Objective/Outcome
Expert
Contributions
to Assessment
learning
objectives
knowledge
1.1 Students demonstrate that they
have basic knowledge in Business
Administration.
Sound knowledge base Class room
of all upcoming and
Interaction
business
relevant
technologies.
Final test
1.2 Students demonstrate their
Focus
on
technologies
distinguished and sound
competencies
in
enabling
Economics.
1.3 Students have command of legal
methodology for case solutions on
basis
of
claims.
1.4 Students are able to solve
business problems by applying
quantitative methods
Use
of
information
technology u
2.1 Students demonstrate proficiency
in using computer programs to solve
business
problems.
n.a.
2.2 Students are able to use
information systems effectively in real
world business settings
Critical thinking and analytical
Competence
3. Students are able to apply
analytical and critical thinking skills to
complex problems
Focus
on
enabling
students to understand
Direct
digitization
and
feedback
transformation processes
student
Ethical
awareness
n.a.
4. Students are able to develop
business ethics strategies and apply
them to typical business decision
-making problems
Communication
Skills
5.1 Students are able to express
complex problems effectively in
writing.
5.2 Students demonstrate their oral
communication skills in presentations
Course is designed and Direct
held in a fully interactive feedback
format. Students will
therefore
develop
competence to clearly
express thoughts and
generate insights.
5.1 Students are able to express
complex problems effectively in
Case studies are
Performed
in
interactive manner
writing.
an
5.2 Students demonstrate their oral
communication skills in presentations
Capacity
for
teamwork
6. Students show that they are able to
work successfully in teams by
performing practical tasks
Short team work tasks
are given.
student
Course structure:
-
Chapter 1: Megatrends in communications & computing
-
Chapter 2: High level overview – emerging technologies
-
Chapter 3: Detailed Overview - Highly relevant technologies
-
Chapter 4: Big data Analytics / Cloud
-
Chapter 5: Artificial Intelligence / Cloud
-
Chapter 6: Connectionless Payment Systems: Technology and Importance
-
Chapter 7: IOT Systems and sensoring
-
Chapter
-
Chapter 9: Transformation and Disruption incl. Case Studies
-
Chapter 10: Data Monetization incl. Case Studies
-
Chapter 11: Bringing it all together: Visionary concepts for the 21st century:
Industry 4.0, smart city, smart utility, self driving cars.
8:
Digitization:
Definition
and
Application
and
Assessment:/
-
The course is assessed by means of a Referat/Hausarbeit
Grading Scale:
For grading details please refer to the Studien und Prüfungsordnung (SPO)
1.0 Very good, a performance significantly above the average
2.0 Good, an above average performance
Case
Studies
3.0 Satisfactory, an average performance
4.0 Adequate, a below average performance with noticeable shortcomings
5.0 Fail, an unacceptable performance
Literature:
Comprehensive Handout
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artificial intelligence ; 12th Pacific Rim International Conference on Artificial Intelligence,
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Aggarwal, Charu C. (2013): Managing and mining sensor data. New York: Springer.
Allums, Skip (2014): Designing mobile payment experiences. Principles and best practices
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Bassi, Alessandro (2013): Enabling things to talk. Designing IoT solutions with the IoT
architectural reference model. Heidelberg: Springer.
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Disrupting the mobile payment industry (2013). Unter Mitarbeit von Deirdre Bolton. New York:
Bloomberg (Business and education in video).
Fathi, Madjid (2013): Integration of practice-oriented knowledge technology. Trends and
prospectives. Berlin, New York: Springer.
Hemann, Chuck; Burbary, Ken (2013): Digital marketing analytics. Making sense of
consumer data in a digital world. Indianapolis, Ind.: Que.
Holler, Jan (2014): From machine-to-machine to the internet of things. Introduction to a new
age of intelligence. Amsterdam: Academic Press.
Hozdić, Elvis: Manufacturing for Industry 4.0.
Kent, Jennifer: Dominant mobile payment approaches and leading mobile payment solution
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decisions and improve performance. Chichester, West Sussex, United Kingdom, Hoboken,
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publication not identified], New York, N.Y., ©2014: NPO/Netherlands Public Broadcast;
distributed by Films Media Group
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Business intelligence and analytic trends for today's businesses. Hoboken, New Jersey: John
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Australia, December 6-9, 2010, Revised selected papers. Berlin, New York: Springer (Lecture
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