MD at Universidade Nova De Lisboa | Flashcards & Summaries

Select your language

Suggested languages for you:
Log In Start studying!

Lernmaterialien für MD an der Universidade Nova de Lisboa

Greife auf kostenlose Karteikarten, Zusammenfassungen, Übungsaufgaben und Altklausuren für deinen MD Kurs an der Universidade Nova de Lisboa zu.

TESTE DEIN WISSEN

What are the 5 Big Data characteristics?

Lösung anzeigen
TESTE DEIN WISSEN

Volume
Variety
Velocity
Variability
Veracity

Lösung ausblenden
TESTE DEIN WISSEN

What is volume in Big Data?

Lösung anzeigen
TESTE DEIN WISSEN

Volume is a characteristic which indicates the magnitude of data

Lösung ausblenden
TESTE DEIN WISSEN

Is is practical to define a specific threshold for the Big data volume? why?

Lösung anzeigen
TESTE DEIN WISSEN

It is impractical to define a specific threshold for Big Data volume, as different types of data require different technologies to deal with it (e.g., tabular data and video data)

Lösung ausblenden
TESTE DEIN WISSEN

What is the main cause for the ever increasing volume?

Lösung anzeigen
TESTE DEIN WISSEN

is the fact that we currently store all our interactions with the majority of services available in our world.

Lösung ausblenden
TESTE DEIN WISSEN

What is Variety in Big Data?

Lösung anzeigen
TESTE DEIN WISSEN

Different types of data.


Data can be classified as:
structured (e.g., transactional data, spreadsheets, relational
databases;
semi-structured (e.g., web server logs and Extensible Markup Language - XML);
unstructured (e.g., social media posts, audio, video, images); 

Lösung ausblenden
TESTE DEIN WISSEN

What are some examples of structured data?

Lösung anzeigen
TESTE DEIN WISSEN

 transactional data, spreadsheets, relational databases

Lösung ausblenden
TESTE DEIN WISSEN

What are some examples of semi-structured data?

Lösung anzeigen
TESTE DEIN WISSEN

web server logs and Extensible Markup Language - XML

Lösung ausblenden
TESTE DEIN WISSEN

What are some examples of unstructured data?

Lösung anzeigen
TESTE DEIN WISSEN

social media posts, audio, video, images

Lösung ausblenden
TESTE DEIN WISSEN

What is velocity in Big Data?

Lösung anzeigen
TESTE DEIN WISSEN

- the rate at which data is generated
- to the speed of analysis and decision support

Lösung ausblenden
TESTE DEIN WISSEN

what are the two different rates at which data is generated?

Lösung anzeigen
TESTE DEIN WISSEN

- batch

- real-time (streaming)

Lösung ausblenden
TESTE DEIN WISSEN

Big Data Impacts

Lösung anzeigen
TESTE DEIN WISSEN

- Digital footprint (produced anyways for free)
- n = N (no sampling, but potential bias)
Data-fusion (unstructured and incomplete)
Real-time (dynamic)
Machine Learning (no need for theory)

Lösung ausblenden
TESTE DEIN WISSEN

Gartner's definition of Big data

Lösung anzeigen
TESTE DEIN WISSEN

Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.

Lösung ausblenden
  • 6990 Karteikarten
  • 637 Studierende
  • 0 Lernmaterialien

Beispielhafte Karteikarten für deinen MD Kurs an der Universidade Nova de Lisboa - von Kommilitonen auf StudySmarter erstellt!

Q:

What are the 5 Big Data characteristics?

A:

Volume
Variety
Velocity
Variability
Veracity

Q:

What is volume in Big Data?

A:

Volume is a characteristic which indicates the magnitude of data

Q:

Is is practical to define a specific threshold for the Big data volume? why?

A:

It is impractical to define a specific threshold for Big Data volume, as different types of data require different technologies to deal with it (e.g., tabular data and video data)

Q:

What is the main cause for the ever increasing volume?

A:

is the fact that we currently store all our interactions with the majority of services available in our world.

Q:

What is Variety in Big Data?

A:

Different types of data.


Data can be classified as:
structured (e.g., transactional data, spreadsheets, relational
databases;
semi-structured (e.g., web server logs and Extensible Markup Language - XML);
unstructured (e.g., social media posts, audio, video, images); 

Mehr Karteikarten anzeigen
Q:

What are some examples of structured data?

A:

 transactional data, spreadsheets, relational databases

Q:

What are some examples of semi-structured data?

A:

web server logs and Extensible Markup Language - XML

Q:

What are some examples of unstructured data?

A:

social media posts, audio, video, images

Q:

What is velocity in Big Data?

A:

- the rate at which data is generated
- to the speed of analysis and decision support

Q:

what are the two different rates at which data is generated?

A:

- batch

- real-time (streaming)

Q:

Big Data Impacts

A:

- Digital footprint (produced anyways for free)
- n = N (no sampling, but potential bias)
Data-fusion (unstructured and incomplete)
Real-time (dynamic)
Machine Learning (no need for theory)

Q:

Gartner's definition of Big data

A:

Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.

MD

Erstelle und finde Lernmaterialien auf StudySmarter.

Greife kostenlos auf tausende geteilte Karteikarten, Zusammenfassungen, Altklausuren und mehr zu.

Jetzt loslegen

Das sind die beliebtesten MD Kurse im gesamten StudySmarter Universum

md english 2

Eastern Mediterranean University

Zum Kurs
R1 MDU

Pontificia Universidad Catolica de Chile

Zum Kurs
MDM

Institut Supérieur de Gestion de Tunis

Zum Kurs
MDNA

Fachhochschule Campus Wien

Zum Kurs
MDM

University of Milan - Bicocca

Zum Kurs

Die all-in-one Lernapp für Studierende

Greife auf Millionen geteilter Lernmaterialien der StudySmarter Community zu
Kostenlos anmelden MD
Erstelle Karteikarten und Zusammenfassungen mit den StudySmarter Tools
Kostenlos loslegen MD