DTM at LMU München

Flashcards and summaries for DTM at the LMU München

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Exemplary flashcards for DTM at the LMU München on StudySmarter:

What is Digital Innovation?


Exemplary flashcards for DTM at the LMU München on StudySmarter:

What are potential triggers for digital innovation? 

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What are the key effects of digital technologies?

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What are the implications of transmitting data from analogue to digital?

Exemplary flashcards for DTM at the LMU München on StudySmarter:

Explain the 3 current trend in cloudcomputing!


Exemplary flashcards for DTM at the LMU München on StudySmarter:

Explain the difference between on-premise and SaaS!

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What are requirements of storing data in databases? 

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What are weaknesses of relational databases?

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What is a data-warehouse system?

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What is big data?

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What exactly is AI?

Exemplary flashcards for DTM at the LMU München on StudySmarter:

What are expert systems?

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Exemplary flashcards for DTM at the LMU München on StudySmarter:

DTM

What is Digital Innovation?


Digital Innovation: „the creation (and consequent change )of market offerings, business processes, or models that result from the use of digital technology” (Nambisan et al. 2017, p. 224).

DTM

What are potential triggers for digital innovation? 
New business requirements trigger the
development of digital innovations
(„technology-pull“)

Novel digital technologies trigger the
development of digital innovations
(„technology-push“)

DTM

What are the key effects of digital technologies?
  • Faster processing of data and allow improved the possibilities to exchange data
  • The steadily increasing speed of exchanging information via the internet is often the basis for this phenomenon 
  • in practices, it is hard to assess what the implications of new digital technology are without having a deeper knowledge about the technical capabilities

DTM

What are the implications of transmitting data from analogue to digital?
Loss of information and therefore a decrease in data quality

DTM

Explain the 3 current trend in cloudcomputing!


SaaS: 

is the term for offering computer applications (software) as a service over the Internet, that is paid by usage. Software is no longer installed and executed but accessed online and used on demand. The supplier therefore not only provides the software, but also accessibility and security of data and applications. Technically these services run mostly in an multi-tenant environment.


PaaS: is an advancement of the SaaS-idea and a term for offering
a development- and runtime-environment of software over the Internet. PaaS-customers
are able to enrich existing solutions with own applications or to develop completely new
applications. The platform offers developers basic functionalities like e.g. integration, user
rights, accessibility and therefore makes development of complex applications a lot easier.

IaaS: 

is a term for a virtual computer infrastructure, that is
offered to the customer as a service. Customers are able to obtain processing and storage
power for applications on demand. In contrast to classical hosting this infrastructure is
offered in an multi-tenant architecture, which enables easy scalability on actual demand.



DTM

Explain the difference between on-premise and SaaS!

Customer is getting software via the internet.
Management and Improvement of the software stays at the vendor side.

DTM

What are requirements of storing data in databases? 

Logical data independence between the used scheme and the application/operator, as well
ass physical data independence between the used scheme and the physical data storage
 Reducing redundancy to a minimum with the help of a logical data structure and by maintaining
the same revision status for multiple stored data (data consistency)
 Data base integrity (correctness/integrity of data): avoiding misentries and unauthorized
procedures (semantical integrity), as well as avoiding errors when several operators use the
same database (operative integrity)
 Preservation of the data from distortion, destruction and unauthorized access (data security),
as well as preventing unauthorized usage of data (data privacy)
 Reliability: establishing routines for the recovery of data consistency after failures (e.g. after the
uncontrolled shut down of a server)

DTM

What are weaknesses of relational databases?
Relational databases teend to be sensitive to errors --> lower data integrity and efficiency

- manipulation of objects is only possible with SQL knowledge --> Working with the database is expensive and complex

- Segmentation: 

an application object is distributed over several relations, which have to be
jointed for each single task (e.g. a new order) --> no part-of-relationships/subcategories


- Artificial primary keys --> additional data without further information increases redundancy

- Data decomposition --> separating data into multiple relations (hard to detect complex correlations and relationships)

- documentation --> without it gets complex and hard to understand

- redundancy --> the duplication of data fosters redundancy and therefore inefficiency




Relational databases tend to be sensitive to errors.
 lower data integrity and efficiency

Relational databases tend to be sensitive to errors.
 lower data integrity and efficiency

DTM

What is a data-warehouse system?

A data warehouse is a subject-oriented, integrated, nonvolatile, and time-variant collection
of data in support of management’s decisions.

DTM

What is big data?

Big Data represents the information assets characterized by such a high volume, velocity and
variety to require specific technology and analytical methods for its transformation into value.

DTM

What exactly is AI?

“For the present purpose the artificial intelligence problem is taken to be that of making a machine behave in
ways that would be called intelligent if a human were so behaving”

DTM

What are expert systems?

 Expert systems (also called knowledge-based systems) are built to solve problems or give
advice by reasoning based on encoded knowledge.
 The rationale of expert systems is to capture knowledge from experts (e.g. by interviewing them)
in a specific task domain and to allow non-experts to draw upon this knowledge.
 The knowledge is stored a separate entity within an expert system (the knowledge base) and
can be updated without adapting the reasoning entity (called inference engine).
 The most commonly applied method to capture knowledge are if-then rules

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