CH5: Data Foundations

Question 1

What is data and why is it important?

Answer 1

Data is information in any form — words, numbers, pictures, or sounds. It’s like fuel for technology: we need it to make decisions, run automations, or train AI.

Example:
A smart assistant like Siri needs data like your voice commands and calendar to help you.

Question 2

What are the main roles we play when working with data?

Answer 2

When working with data, we:
1. Decide where it comes from (input)
2. Decide how it’s processed (rules or AI)
3. Decide what happens next (action/output)

Example:
You might collect customer messages, use AI to sort them, and send responses automatically.

Question 3

What are the three main types of data and how are they different?

Answer 3

Types of data:
- Structured: Like a tidy Excel sheet (easy to search)
- Unstructured: Like a messy pile of photos or texts (hard to search)
- Semi-Structured: Like tagged notes (some structure)

Example:
A spreadsheet = structured, a YouTube video = unstructured, a JSON file = semi-structured.

Question 4

What are the two main types of information: qualitative vs quantitative?

Answer 4

Qualitative data (text): Descriptive, like names or comments.
Quantitative data (numbers): Countable or measurable, like age or scores.

Example:
‘James is happy’ is qualitative. ‘James is 25 years old’ is quantitative.

Question 5

Why is it important to understand different data types?

Answer 5

Knowing your data type helps you know how to store, process, and analyze it. Different types need different tools and methods.

Example:
You wouldn’t store photos the same way you store numbers. One might go in cloud storage, the other in a spreadsheet.

Question 6

What are common data types in systems and code?

Answer 6

Common data types:
- String: Text (‘name’: ‘John’)
- Number: Whole or decimal (‘price’: 9.99)
- Boolean: True or false (‘isMember’: true)
- Array: List of items (‘tags’: [‘fun’, ‘learning’])
- Object: Key-value pair data (‘user’: {‘id’: 1})
- Null: Missing value (‘phone’: null)

Example:
A product might have ‘price’ as a number and ‘name’ as a string.

Question 7

How do data types affect workflow logic?

Answer 7

Data types change how things work in automations:
- Booleans: Help make decisions (if true, do this)
- Arrays: Used to repeat things (like emailing lots of people)
- Numbers: Used for math
- Objects: Used for structured profiles

Example:
If ‘isSubscribed’ is true, send a welcome email.

Question 8

What are the key takeaways for handling data effectively?

Answer 8

Always:
- Check your data outputs
- Convert data types if needed
- Test different cases (like missing info)
- Use tools to clean and format data

Example:
If a user didn’t give a phone number (null), your system should know not to send an SMS.