Intro to data types

Learn how different data types help organize information in your workflows.

Module overview

🥚 Data isn’t one-size-fits-all. Different types of data—like text, numbers, and lists—help computers know how to store, process, and use information efficiently. In this lesson, you’ll explore the most common data types you’ll see in Rewst workflows, making it easier to build and manage automations.

Video (4:58 minutes)

Module summary

What are data types?

Data types are labels that tell computers what kind of information they’re working with. Just like you organize items in your home by category—books, clothes, groceries—computers organize data by type to know how to process it.

Common data types you’ll use in Rewst

Here are the main data types to know:

• Strings: Text, like names, messages, or IDs (e.g., "Hello, world!" or "12345ABC").

• Numbers: Can be whole numbers (integers) or decimals (floats).

• Booleans: Simple yes/no values (e.g., true/false or on/off).

• Lists: Collections of related items (e.g., ["apples", "oranges", "bananas"]).

• Dictionaries: Key-value pairs that organize related information (e.g., "Name": "John Doe", "Age": 30)

Why data types matter in Rewst

Understanding data types helps you navigate Rewst workflows more easily. Each step in a workflow may handle different types of data, and knowing what type you’re working with ensures your automations run smoothly and efficiently.

Action items

• Think about a process you want to automate and list the types of data it would involve. For example, would you need text (strings), numbers, or yes/no decisions (Booleans)? Identifying data types early can help you design more efficient workflows in Rewst.

• Take the data types knowledge check:

Data types knowledge check

Keep on cluckin'

Go to the previous module:

Intro to JSON

Go to the next module:

Reading JSON