Data Wisdom Flashcards

1
Q

What are mental models?

A

They present a framework to understand the vast amount of data landscape surrounding us

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2
Q

DIKW pyramid

A

D - Data
I - Information
K- Knowledge
W- Wisdom

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3
Q

Data

A

Data is the foundation of the pyramid.

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4
Q

Information

A

Is organised data with context. It reveals a whole another level of the pyramid

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5
Q

Knowledge

A

Is connecting all the dots of information in order to understand their relationship. Knowledge is information with meaning

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6
Q

Wisdom

A

Hardest part of the entry pyramid. Transferring knowledge into wisdom requires us to add more meaning to the information at hand and to understand the relationship between each piece of information.

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7
Q

What is decision making?

A

The process to make the right choices at the right time

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8
Q

The process from data to decision

A

1 Ask questions
2 Gather data
3 Prepare data
4 Conduct Analysis
5 Make Decisions

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9
Q

Characteristics of a good question

A

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

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10
Q

How to collect the right data to answer your question

A

• Thinking ahead of your analysis
• Finding the correct data source

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11
Q

Steps to prep data for analysis

A

• Cleaning “bad” data to make it “good”
• Arranging data into expected structure for analysis

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12
Q

List tools that help with data analysis

A

• Python R
• Tableau Power BI
• Excel Google Sheets

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13
Q

Why do we analyse data?

A

So we can make better decisions bases on data

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14
Q

Why can data be overwhelming?

A

Data can be too large when working with it in its raw form

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15
Q

How can aggregation help us?

A

It translates raw data in ways we can understand

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16
Q

How can aggregation appear?

A

As Metrics
Benchmarks
Key performance indicators

17
Q

How can curiosity help with data aggregation?

A

It can help you unlock the value of data and its impact

18
Q

Data flow is highly complex. List a few characteristics of data flows.

A

• It can be data from many different source systems
• Processed through other systems
• Display and manipulate in other systems

19
Q

What are the data domains?

A

• Data governance
• Data quality
• Data privacy and security