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Introduction to Data Flashcards

1
Q

Two main formats of data?

A

Structured and Unstructured

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2
Q

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

A

Datum, given/facts

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3
Q

Structured data is ______, ______, _______, _______.

A

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

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4
Q

Unstructured data is ______, ______, _______, _______.

A

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

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5
Q

Examples of unstructured data

A

Reports and email messages
Surveillance videos

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6
Q

Quantitative data is also called

A

Numerical Data

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7
Q

Quantitative data can be

A

count, measure, represent with numbers

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8
Q

Qualitative data is also called

A

categorical data

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9
Q

Qualitative data can be

A

group into categories

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10
Q

Data does not tell anything without context.

A

True

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11
Q

Data context refers to

A

information that provides meaning to data

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12
Q

Characteristics of data:

A

Time frame
Location and source

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13
Q

Characteristics of the data are also called

A

Metadata

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14
Q

What is the goal of data in organizations?

A

Support Business Objectives

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15
Q

Data can help organizations by?

A

Improving decision making

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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

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17
Q

How does data help in healthcare?

A

Monitor Personal Data

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18
Q

What is supply chain?

A

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

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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

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20
Q

What is the goal of data in supply chain?

A

Make sense of the massive amount of generated data

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21
Q

Metrics used to optimize supply chain?

A

Average Inventory
Inventory turnover ratio

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22
Q

What is inventory turnover ratio?

A

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

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23
Q

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

A

Demand Forecasting

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24
Q

How does data help in education?

A

User feedback

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25
What does the DIKW pyramid stand for?
Data Information Knowledge Wisdom
26
This pyramid highlights the journey data takes in order to become valuable wisdom.
DIKW pyramid
27
What is the foundation of the DIKW pyramid?
Data
28
Data without context?
Raw Data
29
_________ is (organized) data with context.
Information
30
______ is a higher level of understanding than data and is created by adding context to data.
Information
31
_________ is information with meaning.
Knowledge
32
Transforming data to _______ is the hardest part of the entire pyramid.
Wisdom
33
Add more meaning to the information at hand and understand the relationships between each piece of information.
Transforming knowledge into wisdom
34
Allows us to make decisions and apply our knowledge the world around us.
Wisdom
35
What is decision making?
Decision making is the process to make the right choices at the right time.
36
Data driven decision making is a five-step process, name the five steps.
01 - Ask Question 02 - Gather Data 03 - Prepare Data 04 - Conduct Analysis 05 - Make Decision
37
The journey of a data-driven process starts with ________________.
Identifying the question you are looking to answer.
38
A good question will
Outline exact what you are looking to answer Prevent scope creep Ensure success throughout the rest of the process
39
Collecting data is finding out _____________.
where you should source your data
40
Preparing data can mean many things:
Clean bad to good data Arrange data into expected structure for analysis
41
In some cases the ___________ phase can be the most cumbersome taking up to 80% of the overall time for the entire decision making process.
data preparation
42
This step is critical because it is what transforms our data into something we can make decisions with.
Analyzing data
43
This step is ultimately interpreting the results and making a decision.
Making decisions
44
This whole process is also iterative in nature.
Making decisions
45
In order to solve the burden of overwhelming data, what should you do?
Summarize the data into smaller pieces of information to make informed decisions.
46
What translate raw data into summaries that are easier to understand?
Aggregations
47
Common aggregations:
Simple average (mean) Totals aka sums Minimums and Maximums Modes
48
Aggregations allow you to focus on
A specific attribute of a dataset
49
Aggregations appear in many ways throughout organizations:
Metrics Benchmarks KPIs (Key Performance Indicators)
50
The field of ________ is responsible for overseeing and coordinating all the subdomains into one unifying structure
Data Management
51
seeks to ensure that data is consistent, trustworthy, and isn’t misused.
Data Governance
52
Ensures that data is accurate, valid, complete, and consistent.
Data Quality
53
go hand in hand to oversee data access, use and protection.
Data Privacy and Security
54
Ensures that data is collected, stored, and used ethically
Data ethics
55
Principles of data ethics:
1. Permission for data collection 2. Transparency about the plan 3. Privacy of data 4. Good Intentions 5. Consider the outcome
56
Asking for user consent before collecting data. Users are in control of their data.
Permission
57
Being transparent of how you plan to use, store, and collect data
Transparency
58
Lack of transparency may lead to reputation and legal damage.
True
59
Refers to secluding (information about) yourself
Privacy
60
Requires individuals to be in control of how their data is collected and used.
Data Privacy
61
What does PII mean?
Personal Identifiable Information
62
Individual Responsibilities for Privacy Protection:
Strong Passwords Up-to-date operating systems Cautionary Internet Browsing
63
How to prevent data breaches:
Limit sharing sensitive data Pseudo data anonymization
64
Data is collected for the right reasons Question yourself about the reasons you collect data
Intentions
65
Are there consequences of my actions? Protecting vulnerable populations
Outcomes
66
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.
Data ethics
67
a framework to regulate data from its collection to its use, analysis, and disposal.
Data Life cycle
68
Steps in the Data Life Cycle?
Planning and Collecting Storing and Managing Cleaning and Processing Analyzing and visualizing Sharing Archiving/destroying
69
Why is data life cycle important?
Ensure data is regulated responsibly Identify potential areas for improvement Improve efficiency and effectiveness of operations
70
What part of the Data Lifecycle stage focuses on sharing of roles and responsibilities?
Plan and collect stage
71
What part of the Data Life cycle stage is where you need to prepare a business question that answers the need of your stakeholders
Plan and collect stage
72
What part of the Data Life Cycle Stage seeks to achieve optimal results in terms of time and cost?
Plan and collect stage
73
What part of the Data Lifecycle stage also focuses on collecting or creating data?
Plan and collect stage
74
What Data Lifecycle stage manages data stored in databases or data warehouses?
Store and Manage stage
75
What part of the Data Lifecycle stage ensures that the data is easily accessible to the right person and can be managed overtime?
Store and Manage stage
76
What data lifecycle stage includes Removal of PII?
Store and Manage stage
77
How to clean and process data before proper data analysis
Formatting data Dealing with missing values or errors Transforming data into a more usable form
78
What part of the data lifecycle stage focuses on analyzing raw data for new insights?
Analyze and Visualize stage
79
Data is easier to interpret when visualized
True
80
What part of the data lifecycle stage focuses on Communicating your results with stakeholders?
Share stage
81
Example of sharing insights
Dashboards, reports, papers
82
What part of the data lifecycle stage focuses on when to kept or delete data?
Archive or destroy stage
83
Data archiving can be met with the following:
Data Backups Documentations Digitizing
84
Data destruction is done on rare cases. This is done to what?
Protect private information Resources can be freed up
85
Common mistakes about data:
Not having a clear goal or question Insufficient or wrong data Lack of appropriate analysis No clear communication of results
86
The data sample doesn't represent all the data.
Data Bias
87

Data Literacy (9 decks)

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