Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Data Literacy > Introduction to Data > Flashcards

Introduction to Data Flashcards

1
Q

Two main formats of data?

A

Structured and Unstructured

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Data is dericed from the word _______, which means _________.

A

Datum, given/facts

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Structured data is ______, ______, _______, _______.

A

Organized, easy to manage
Tabular Format
Predefined structure
Text and Numbers

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Unstructured data is ______, ______, _______, _______.

A

Unorganized, difficult to manage
No specific format
No predefined structure
Text, images, audio, video

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Examples of unstructured data

A

Reports and email messages
Surveillance videos

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Quantitative data is also called

A

Numerical Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Quantitative data can be

A

count, measure, represent with numbers

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Qualitative data is also called

A

categorical data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Qualitative data can be

A

group into categories

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Data does not tell anything without context.

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Data context refers to

A

information that provides meaning to data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Characteristics of data:

A

Time frame
Location and source

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Characteristics of the data are also called

A

Metadata

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is the goal of data in organizations?

A

Support Business Objectives

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Data can help organizations by?

A

Improving decision making

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

How can Data help business organizations?

A

Profitability
Social Good
Research
Customer Satisfaction and Employee Happiness
Measure ROI (Return on Investments)
Optimize processes and find new opportunities

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

How does data help in healthcare?

A

Monitor Personal Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What is supply chain?

A

The sequence of processes involved in the production and distribution of a product.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What is the goal of data in healthcare?

A

Detect and prevent health problems
Turn patient care into precision medicine
Advancing healthcare research worldwide

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What is the goal of data in supply chain?

A

Make sense of the massive amount of generated data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Metrics used to optimize supply chain?

A

Average Inventory
Inventory turnover ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

What is inventory turnover ratio?

A

Calculates how often a company has sold and replaced inventory during a given period.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Common analytics technique used in supply chain to predict whether the right products will be in stock in time?

A

Demand Forecasting

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

How does data help in education?

A

User feedback

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

What does the DIKW pyramid stand for?

A

Data
Information
Knowledge
Wisdom

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

This pyramid highlights the journey data takes in order to become valuable wisdom.

A

DIKW pyramid

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

What is the foundation of the DIKW pyramid?

A

Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

Data without context?

A

Raw Data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

_________ is (organized) data with context.

A

Information

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

______ is a higher level of understanding than data and is created by adding context to data.

A

Information

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

_________ is information with meaning.

A

Knowledge

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

Transforming data to _______ is the hardest part of the entire pyramid.

A

Wisdom

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

Add more meaning to the information at hand and understand the relationships between each piece of information.

A

Transforming knowledge into wisdom

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

Allows us to make decisions and apply our knowledge the world around us.

A

Wisdom

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

What is decision making?

A

Decision making is the process to make the right choices at the right time.

36
Q

Data driven decision making is a five-step process, name the five steps.

A

01 - Ask Question
02 - Gather Data
03 - Prepare Data
04 - Conduct Analysis
05 - Make Decision

37
Q

The journey of a data-driven process starts with ________________.

A

Identifying the question you are looking to answer.

38
Q

A good question will

A

Outline exact what you are looking to answer
Prevent scope creep
Ensure success throughout the rest of the process

39
Q

Collecting data is finding out _____________.

A

where you should source your data

40
Q

Preparing data can mean many things:

A

Clean bad to good data
Arrange data into expected structure for analysis

41
Q

In some cases the ___________ phase can be the most cumbersome taking up to 80% of the overall time for the entire decision making process.

A

data preparation

42
Q

This step is critical because it is what transforms our data into something we can make decisions with.

A

Analyzing data

43
Q

This step is ultimately interpreting the results and making a decision.

A

Making decisions

44
Q

This whole process is also iterative in nature.

A

Making decisions

45
Q

In order to solve the burden of overwhelming data, what should you do?

A

Summarize the data into smaller pieces of information to make informed decisions.

46
Q

What translate raw data into summaries that are easier to understand?

A

Aggregations

47
Q

Common aggregations:

A

Simple average (mean)
Totals aka sums
Minimums and Maximums
Modes

48
Q

Aggregations allow you to focus on

A

A specific attribute of a dataset

49
Q

Aggregations appear in many ways throughout organizations:

A

Metrics
Benchmarks
KPIs (Key Performance Indicators)

50
Q

The field of ________ is responsible for overseeing and coordinating all the subdomains into one unifying structure

A

Data Management

51
Q

seeks to ensure that data is consistent, trustworthy, and isn’t misused.

A

Data Governance

52
Q

Ensures that data is accurate, valid, complete, and consistent.

A

Data Quality

53
Q

go hand in hand to oversee data access, use and protection.

A

Data Privacy and Security

54
Q

Ensures that data is collected, stored, and used ethically

A

Data ethics

55
Q

Principles of data ethics:

A
  1. Permission for data collection
  2. Transparency about the plan
  3. Privacy of data
  4. Good Intentions
  5. Consider the outcome
56
Q

Asking for user consent before collecting data. Users are in control of their data.

A

Permission

57
Q

Being transparent of how you plan to use, store, and collect data

A

Transparency

58
Q

Lack of transparency may lead to reputation and legal damage.

A

True

59
Q

Refers to secluding (information about) yourself

A

Privacy

60
Q

Requires individuals to be in control of how their data is collected and used.

A

Data Privacy

61
Q

What does PII mean?

A

Personal Identifiable Information

62
Q

Individual Responsibilities for Privacy Protection:

A

Strong Passwords
Up-to-date operating systems
Cautionary Internet Browsing

63
Q

How to prevent data breaches:

A

Limit sharing sensitive data
Pseudo data anonymization

64
Q

Data is collected for the right reasons
Question yourself about the reasons you collect data

A

Intentions

65
Q

Are there consequences of my actions?
Protecting vulnerable populations

A

Outcomes

66
Q

is a branch of ethics that deals with the moral problems related to data. It is a code of behavior that specifies what is right and wrong in the handling of data.

A

Data ethics

67
Q

a framework to regulate data from its collection to its use, analysis, and disposal.

A

Data Life cycle

68
Q

Steps in the Data Life Cycle?

A

Planning and Collecting
Storing and Managing
Cleaning and Processing
Analyzing and visualizing
Sharing
Archiving/destroying

69
Q

Why is data life cycle important?

A

Ensure data is regulated responsibly
Identify potential areas for improvement
Improve efficiency and effectiveness of operations

70
Q

What part of the Data Lifecycle stage focuses on sharing of roles and responsibilities?

A

Plan and collect stage

71
Q

What part of the Data Life cycle stage is where you need to prepare a business question that answers the need of your stakeholders

A

Plan and collect stage

72
Q

What part of the Data Life Cycle Stage seeks to achieve optimal results in terms of time and cost?

A

Plan and collect stage

73
Q

What part of the Data Lifecycle stage also focuses on collecting or creating data?

A

Plan and collect stage

74
Q

What Data Lifecycle stage manages data stored in databases or data warehouses?

A

Store and Manage stage

75
Q

What part of the Data Lifecycle stage ensures that the data is easily accessible to the right person and can be managed overtime?

A

Store and Manage stage

76
Q

What data lifecycle stage includes Removal of PII?

A

Store and Manage stage

77
Q

How to clean and process data before proper data analysis

A

Formatting data
Dealing with missing values or errors
Transforming data into a more usable form

78
Q

What part of the data lifecycle stage focuses on analyzing raw data for new insights?

A

Analyze and Visualize stage

79
Q

Data is easier to interpret when visualized

A

True

80
Q

What part of the data lifecycle stage focuses on Communicating your results with stakeholders?

A

Share stage

81
Q

Example of sharing insights

A

Dashboards, reports, papers

82
Q

What part of the data lifecycle stage focuses on when to kept or delete data?

A

Archive or destroy stage

83
Q

Data archiving can be met with the following:

A

Data Backups
Documentations
Digitizing

84
Q

Data destruction is done on rare cases. This is done to what?

A

Protect private information
Resources can be freed up

85
Q

Common mistakes about data:

A

Not having a clear goal or question
Insufficient or wrong data
Lack of appropriate analysis
No clear communication of results

86
Q

The data sample doesn’t represent all the data.

A

Data Bias

87
Q
A

Data Literacy (9 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions