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Digital Ecosystem > Session 3 > Flashcards

Session 3 Flashcards

1
Q

Data

A
  • Raw facts
  • Just numbers(s) and /or text
  • Context is not always provided
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2
Q

Information

A
  • Data with context
  • Processed data
  • Value-added to data (Summarized, Organized, Analyzed)
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3
Q

Data transformation

A
  • Organizing (re-grouping, clustering)
  • Analysing (summarizing, manipulating)
  • Contextualizing (giving meaning, sense, setting)
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4
Q

Propreties of information

A
  • Intagibility & non-rivalrousness
  • Multiple re-uses
  • Use/exploitation is capability-based
  • Information asymmetry
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5
Q

Why does digital ecosystems providers exploit information asymmetries ?

A

Because that imbalance means that the side with more, better or unique information enjoys a competitive advantage over others.

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6
Q

Structured data

A

Follows strict norms and conventions which make it easy to store and query

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7
Q

Unstructured data

A

Do not follow strict norms and conventions, which make it harder to store and query

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8
Q

What are the 2 types of Quantitative data ?

A
  • Discrete data
  • Contininuous data
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9
Q

Discrete data

A
  • The number of students in a class
  • The number of workers in a company
  • The number of home runs in a baseball game
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10
Q

Continuous data

A
  • The height of children
  • The square footage of a two-bedroom house
  • The speed of cars
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11
Q

Qualitative data

A

Descriptive or non-numerical data used to describe and understand characteristics, attributes, or experiences

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12
Q

What are the 2 types of Qualitative data ?

A
  • Nominal data
  • Ordinal data
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13
Q

Nominal data

A

Categorical data that has no inherent order or rank. It can take on any value from a set of categories, but the categories themselves have no specific meaning or order (ex: gender, hair color, ethinicty)

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14
Q

Ordinal data

A

Categorical data that has a natural order or ranking. Unlike nominal data, ordinal data categories have a specific meaning and order (ex: first, second and third; letter grades; economic status)

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15
Q

Types of data ownership:

A
  • Organizational data
  • Public or open data
  • Personal data
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16
Q

Organizational data

A

Data that is privately owned by companies (Transaction data, Social media data, Clickstream data, System logs)

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17
Q

Public or open data

A

Data that is publicly available and accessible by everyone

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18
Q

Personal data

A

Data belonging or private to individual / person. Data that can be used to identify person (date of birth, fingerprints, DNA, income, address, health information)

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19
Q

Relational Databases

A

Data model based on storing data as an organized collection of interrelated tables containing data

20
Q

Data warehouse

A

Digital storage system that connects large amounts of structured organizational data from many different sources : store current and historical data in one place (single source of truth for an organization)

21
Q

Data lake

A

Digital storage system that conncets large amouths of unstructured data from many different sources

22
Q

Metadata

A

“Data about data”

23
Q

Business metadata

A

Adds context to your data

24
Q

Technical metadata

A

Describes how to access data - including how it is structured

25
Q

Big Data

A

Data sets that are so large or complex that it is difficult to process using traditional database management tools or data processing application

26
Q

Main challenges of Big Data

A
  • Capture
  • Storage
  • Search
  • Analysis
  • Transfer
  • Visualization
  • Data privacy
27
Q

Big data puts a focus on what ?

A
  • Unstructured data (social media, audio and video streams, clickstreams)
  • Data storage (“the cloud”)
  • Data access (via APIs)
28
Q

Thanks to which technology big data is possible ?

A

Machine learning and AI

29
Q

5 characteristics of Big Data

A
  • Volume
  • Variety
  • Variability
  • Velocity
  • Veracity
  • Value
30
Q

Who is generating Big Data ?

A
  • Media
  • Cloud
  • Web
  • IoT
  • Databases
31
Q

Big Data (Volume)

A

A lot of data (around 10 sextillion)

32
Q

Big Data (Variety)

A

Different forms of data, genreated and stored in different ways

33
Q

Big Data (Variability)

A

Variability refers to the changing nature of the form of data and the way it is used over time.

34
Q

Big Data (Velocity)

A

The speed at which data is generated and processed is very fast (social media, websites, AI bots)

35
Q

Big Data (Veracity)

A

Veracity refers to the Truthfulness, accuracy, and reliability of data being collected, stored, and analyze -> Big Data is messy, noise, and error-prone

36
Q

Big Data (Value)

A

The worth or usefulness of data for a particular purpose (supporting research, driving innovation and revenue, reducing costs)

37
Q

Valuable uses of Big Data

A
  • Tracking consumer behaviour and shopping habits to deliver hyper-personalized retail product recommendations
  • Monitoring payment patterns to detect fraud in real time
38
Q

Data Storage

A

Methods and technologies used to store and retain digital information (traditional or newer methods)

39
Q

Traditional methods

A
  • Hard Disk Drive (HDD)
  • Solid-state drive (SSD)
40
Q

Newer methods

A

Cloud computing

41
Q

Cloud Storage

A

A method of storing data on remote servers accessed over the internet, rather than on a local computer system or physical storage device.

42
Q

What is the CSP ?

A

Cloud Service Provide

43
Q

Benefits of cloud storage

A
  • Scalability
  • Accessibility
  • Cost-effectiveness
44
Q

Where is the data in the cloud stored ?

A

Data Centers

45
Q

What are the 3 types of Cloud Computing ?

A
  • laaS (Infrastructure as a Service)
  • PaaS (Platform as a Service)
  • SaaS (Software as a Service)
46
Q

What are the 3 main cloud computing companies ?

A
  • Amazon web services
  • Azure
  • Google Cloud

Digital Ecosystem (5 decks)

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