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DIGITAL ANALYTICS > Topic 2: Variables and Data > Flashcards

Topic 2: Variables and Data Flashcards

1
Q

characteristic of members of a population

A

Variables

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2
Q

observations of variable

A

Data

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3
Q

contains variables and observations (arrows & columns)

A

Data sets

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4
Q

Data that can be measures with Numbers

A

Quantitative

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5
Q

Data that can be measure with Non-numerical data

A

Qualitative

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6
Q

Whole number that can’t be broken down

A

Discrete

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7
Q

number that can be broken down eg. Height

A

Continuous

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8
Q

Number with known difference between variables eg. time (No true zero)

A

Interval

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9
Q

Number that have measurable intervals where difference can be determined e.g height (Has True Zero)

A

Ratio

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10
Q

Data use for naming variables eg. Hair color

A

Nominal

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11
Q

Data used to describe order of values

A

Ordinal

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12
Q

(4) Consumer analytics data (ADBI)

A

Attitudinal; Descriptive; Behavioral; Interactive

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13
Q

DATA COLLECTION METHODS USED IN ANALYTICS (Sources of Data)

A

•Surveys
• Transactional Tracking (POS System)
• Interview and Focus groups
• Observation
• Online Tracking (Internet Cookies)
• Forms

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14
Q

collected directly from users by your organization (consumer data)

A

first-party data

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15
Q

Sources of first-party data include:

A
  • Website or app behavior
  • Email and newsletter subscribers
  • Lead generation campaigns
  • Surveys
  • Social media
  • Subscriptions
  • Customer feedback
  • Customer service/sales conversations
  • Online chat
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16
Q

Benefits of First-party data

A
  • Personalization and integration
  • Target the right customers
  • Accuracy and control
  • Strengthen customer relationships
  • Compliance with privacy laws (GDPR & DPA)
  • Lower cost
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17
Q

Six effective ways to use your first-party data (consumer data) -SPELLA

A

Social Media; Paid ads; Email; Loyalty programs; Landing Pages; Account based marketing

18
Q

data shared by another organization about its customers (or its first-party data)

A

Second-party data

19
Q

data that’s been aggregated and rented or sold by organizations that don’t have a connection to your company or users

A

third-party data

20
Q

Benefits of Second-party data

A

-It enables you to scale by connecting with new audiences that match your own audience data.
- Combine it with your first-party data to build improved predictive models.
- You can develop better audience insights by analyzing a more extensive audience group.

21
Q

Data Quality (VACCU)

A

Validity; Accuracy; Completeness; Consistency; Uniformity

22
Q

Ensure your data is close to the true values.

A

accuracy

23
Q

If it measures what it is supposed to measure

A

validity

24
Q

The degree to which all required
data is known.

A

completeness

25
Q

Ensure your data is consistent within the same dataset and/or across multiple data sets.

A

consistency

26
Q

The degree to which the data is specified using the same unit of measure.

A

uniformity

27
Q

(4) Data Preparation

A

Data cleansing; Scripting; Data transformation; Data warehousing

28
Q

is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset.

A

Data cleansing

29
Q

A script is a series of Analytics commands that are executed sequentially and used to automate work within

A

Scripting

30
Q

ETL process (Extract, Load, Transform). or to extract data from a source, convert it into a usable format, and deliver it to a destination.

A

Data transformation

31
Q

a central repository of information that can be analyzed to make more informed decisions

A

Data warehousing

32
Q

Data Life Cycle (6)

A

Create-Store-Use-Share-Archive-Destroy

33
Q

Data that cannot be counted, measured or easily expressed using numbers

A

Qualitative

34
Q

Information a company collects directly from its customers and owns

A

First-party data

35
Q

The process of cleaning and transforming raw data prior to processing and analysis.

A

Data preparation

36
Q

Any information collected by an entity that does not have a direct relationship with the user the data is being collected on.

A

Third-party data

37
Q

Indicates how reliable a given dataset is across key dimensions like completeness, consistency, accuracy, and more

A

Data quality

38
Q

Information all about consumers, from their household, demographic and lifestyle details to their behavior and buying

A

(Consumer analytics data)

39
Q

A numerical type of data that includes whole, concrete numbers with specific and fixed data values determined by counting.

A

Discrete

40
Q

Ensure your data is consistent within the same dataset and/or across multiple data sets.

A

Consistency

41
Q

Data that can take any value (Infinite numbers)

A

Continuous

42
Q

Data that can be counted or measured in numerical values.

A

Quantitative

DIGITAL ANALYTICS (5 decks)

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