Master String to Data Type Conversions in Power Automate

When working with Power Automate, data is often received as text (string) from various sources such as SharePoint, Excel, Forms, APIs, Dataverse, and JSON payloads. However, many actions require specific data types like Integer, Float, Boolean, Date, Array, or Object. Therefore, converting strings into appropriate data types is an essential skill for building efficient flows.

In this article, we'll explore how to convert string values into different data types using Power Automate expressions.

Why Convert Data Types?

Data type conversion helps:

• Prevent flow errors
• Improve data accuracy
• Support calculations
• Enable filtering and conditions
• Process API responses correctly
• Improve automation reliability

Prerequisites

Before starting:

• Power Automate Environment
• Basic understanding of Expressions
• Sample string values

Example Input:

"100"
"99.99"
"true"
"2025-06-17"
"[1,2,3]"
{"Name":"John","Age":30}

Convert String to Integer

Suppose the string value is:

"100"

Use the following expression:

int('100')

Output:

100

This converts the string into an Integer data type.

Convert String to Float

String Value:

"99.99"

Expression:

float('99.99')

Output:

99.99

Useful for currency and decimal calculations.

Convert String to Boolean

String Value:

"true"

Expression:

bool('true')

Output:

true

Another example:

bool('false')

Output:

false

Convert String to Date

String Value:

"2025-06-17"

Expression:

formatDateTime('2025-06-17','dd-MM-yyyy')

Output:

17-06-2025

You can use different date formats based on your business requirements.

Convert String to Array

String Value:

"[Apple,Orange,Mango]"

Expression:

json('["Apple","Orange","Mango"]')

Output:

["Apple","Orange","Mango"]

The string is converted into an Array object.

Convert String to JSON Object

String Value:

{"Name":"John","Age":30}

Expression:

json('{
"Name":"John",
"Age":30
}')

Output:

{"Name":"John","Age":30}

This converts the string into a usable JSON object.

Convert String to Number Using Compose

Example:

"500"

Expression:

int(outputs('Compose'))

Output:

500

This method is commonly used when values come dynamically from previous actions.

Real-Time Example

Suppose a Microsoft Form returns:

{"EmployeeID":"1001","Salary":"50000.50","IsActive":"true"}

Convert values:

• EmployeeID: int(EmployeeID)
• Salary: float(Salary)
• ActiveStatus: bool(IsActive)

These conversions allow Power Automate to process the data correctly.

Common Conversion Functions

Benefits

• Better Data Processing: Ensures correct data formats.
• Accurate Calculations: Supports mathematical operations.
• Improved Flow Stability: Reduces runtime failures.
• Enhanced API Integration: Processes JSON responses effectively.
• Simplified Automation: Makes complex workflows easier to manage.

Best Practices

• Validate Input Values: Always check values before conversion.
• Use Compose Actions: Test expressions using Compose.
• Handle Null Values:

  Example:

  coalesce(triggerBody()?['Amount'],0)

• Use Try-Catch Logic: Handle unexpected data formats gracefully.
• Test with Different Inputs: Verify results using multiple scenarios.

Common Use Cases

• SharePoint Data Processing: Convert text fields into numbers.
• Excel Calculations: Perform mathematical operations.
• API Integrations: Process JSON payloads.
• Dataverse Updates: Update numeric and Boolean fields.
• Approval Workflows: Convert and validate user input values.

Conclusion

Data type conversion is one of the most commonly used techniques in Power Automate. Whether you're working with SharePoint, Dataverse, Excel, APIs, or Forms, converting string values into Integer, Float, Boolean, Date, Array, or JSON formats ensures your flows run smoothly and efficiently.

By using built-in Power Automate expressions like int(), float(), bool(), and json(), you can create robust automations that handle data accurately and reliably.