Course 2, Module 1

Question 1

What is structured thinking?

Answer 1

The process of recognizing the current problem or situation, organizing available information, revealing gaps and opportunities, and identifying the options.

Question 2

What is a target audience?

Answer 2

The specific people you’re trying to communicate with.

Question 3

Meaning of cleaning data?

Answer 3

To eliminate inaccuracies by transforming the data into a more useful format and removing outliers. Data cleaning takes place during the process step of the data analysis process.

Question 4

What are the 6 problem types data analysts typically work with?

Answer 4

1. Making predictions - Using data to make informed decisions about how things may be in the future.
2. Categorizing things - Grouping data based on common features.
3. Spotting something unusual - Identifying data that is different from the norm.
4. Identifying themes - Recognizing broader concepts and trends from categorized data.
5. Discovering connections - Identifying similar challenges across different entities—and using data and insights to find common solutions.
6. Finding patterns - Using historical data about what happened in the past to understand how likely it is to happen again.

NOTE - Categorizing things involves assigning items to categories; identifying themes takes those categories a step further by grouping them into broader themes.

Question 5

What are 3 types of bad questions?

Answer 5

1. Leading questions - questions that only have a particular response (e.g. This product is too expensive, isn’t it?)
2. Close-ended questions - Questions that ask for a one-word or brief response only (e.g. Were you satisfied with the customer trial?)
3. Vague questions - Questions that aren’t specific or don’t provide context (e.g. Does the tool work for you?)

Question 6

Effective questions follow the SMART methodology? What does it stand for?

Answer 6

Specific: Is the question specific? Does it address the problem? Does it have context? Will it uncover a lot of the information you need?

Measurable: Will the question give you answers that you can measure?

Action-oriented: Will the answers provide information that helps you devise some type of plan?

Relevant: Is the question about the particular problem you are trying to solve?

Time-bound: Are the answers relevant to the specific time being studied?

Question 7

What is fairness?

Answer 7

Ensuring that your questions don’t create or reinforce bias.

Question 8

When working with data, there are 3 core roles. What are they?

Answer 8

1. Data analysts
2. Data engineers
3. Data scientists