Analytical skills

Question 1

Define analytical skills.

Answer 1

Qualities and characteristics associated with solving problems using data.

Question 2

1/5

Name one analytical skill mentioned in this course

where does it all begin, where do many questions originate from?

Answer 2

curiosity

Question 3

Expound on curiousity as an analytical skill.

Answer 3

It is seeking out new challenges or knowledge.

Question 4

2/5

Name another analytical skill mentioned in this course.

What surrounds the data?

Answer 4

Understanding context.

Question 5

Define context as mentioned in the course.

Answer 5

The condition(s) in which something exists or happens.

e.g. number set

Question 6

3/5

Name another essential analytical skill

Answer 6

Having a technical mindset

Question 7

What does having a technical mindset entail?

Answer 7

the ability to apply analytical methodologies/techniques to solve a real world problem.

being methodical

Question 8

Why is having technical knowledge/techniques crucial?

like having knowledge of tools and troubleshooting manuals.

Answer 8

It helps one to define which approach/methodologies to use and how to work in each resulting step.

the mindset is then one’s ability to apply them.

Question 9

What are three advantages of having a technical midnset for a data analyst?

Answer 9

Enables them to:
1. translate problems into related metrics to be explored
2. break down analytical tasks
3. deliver practical solutions with statistical rigor.

Question 10

What does having systems thinking skill help one with?

Answer 10

It helps one understand data as a part of the whole product flow with real world transactions

Question 11

Why is computational thinking another important skill to have?

Answer 11

It helps data analysts solve problems logically.

since problems are more complex and ambiguous now.

Question 12

What are the 4 steps of computational thinking?

Answer 12

1. Decomposition- break problem down
2. Pattern recognition
3. Abstraction- only focusing on what is important
4. Algorithms- design a step by step solution to problem

useful in analyses.

Question 13

Case study: Applying computational thinking to identify factors driving customer satisfaction in an e-commerce site.

Answer 13

• Decomposition- identifying customer touch points in the site which contribute to customer satisfaction
• Pattern recognition- define known proxy metrics to each touchpoint and look into customer review data.
• Abstraction- ignoring irrelevant data e.g. those that rate experience due to prices and not the site iself
• Algorithms- A data model with touchpoint metrics as input can be developed to survey or estimate what satisfaction score will be.

Question 14

What are 2 ways to cultivate computational thinking?

Answer 14

1. Practice case studies and in day to day
2. Have discussions

Question 15

What are two ways of cultivating systems thinking in data analysis?

Answer 15

1. ensure to look at data flow charts/diagrams.
2. test the product

Question 16

4/5

Name another essential analytical skill mentioned in this course.

explain it with an example

Answer 16

Data design - how data is oranized.

how data is organized in a phonebook for example

Question 17

5/5

Name another essential analytical skill mentioned in this course.

Answer 17

data strategy

Question 18

What does data strategy entail

one’s strategy

Answer 18

management of processes,tools and people in data analysis

the how, the what and the who