Flat vs Nested JSON Conversion - Deep Dive into Conversion Modes

Welcome to part 6 of our JSON to Excel series! In our previous post, we explored the JSON formats that JSON to Excel supports. Today, we're diving deep into the two conversion modes: Flat JSON Mode and Nested JSON Mode. Understanding these modes is crucial for getting the best results from your JSON to Excel conversions.

The Two Conversion Modes

JSON to Excel offers two distinct conversion modes, each designed for different types of JSON structures:

Flat JSON Mode: For simple, non-nested JSON structures
Nested JSON Mode: For complex JSON with nested objects

Choosing the right mode can make the difference between a clean, usable Excel spreadsheet and one that's difficult to work with.

Flat JSON Mode

What is Flat JSON Mode?

Flat JSON Mode is designed for simple JSON structures where each object contains only primitive values (strings, numbers, booleans, null) and no nested objects or arrays that need to be expanded.

When to Use Flat JSON Mode

Use Flat JSON Mode when your JSON:

Has simple key-value pairs
Contains no nested objects
Has arrays that you want to keep as strings
You want a straightforward, one-level Excel structure

Example JSON for Flat Mode

json 复制代码

[
  {
    "id": 1,
    "name": "John Doe",
    "email": "john@example.com",
    "age": 30,
    "active": true
  },
  {
    "id": 2,
    "name": "Jane Smith",
    "email": "jane@example.com",
    "age": 25,
    "active": false
  }
]

Flat Mode Conversion Result

id	name	email	age	active
1	John Doe	john@example.com	30	TRUE
2	Jane Smith	jane@example.com	25	FALSE

Handling Arrays in Flat Mode

When your JSON contains arrays, Flat Mode converts them to string representations:

json 复制代码

[
  {
    "id": 1,
    "name": "John",
    "tags": ["developer", "manager"],
    "scores": [85, 92, 78]
  }
]

Result:

id	name	tags	scores
1	John	["developer","manager"]	[85,92,78]

Handling Nested Objects in Flat Mode

Nested objects are converted to JSON string representations:

json 复制代码

[
  {
    "id": 1,
    "name": "John",
    "contact": {
      "email": "john@example.com",
      "phone": "555-1234"
    }
  }
]

Result:

id	name	contact
1	John	{"email":"john@example.com","phone":"555-1234"}

Pros of Flat Mode

Simplicity: Easy to understand and use
Preserves Structure: Nested data is kept intact as strings
Fast Processing: Quick conversion for simple structures
Predictable Output: Consistent, one-level Excel structure

Cons of Flat Mode

Limited Analysis: Nested data can't be easily analyzed
String Manipulation: Need to parse strings to access nested data
Not Ideal for Complex Data: Doesn't leverage Excel's tabular structure for nested data

Nested JSON Mode

What is Nested JSON Mode?

Nested JSON Mode is designed for complex JSON structures with nested objects. It flattens nested structures into a tabular format, making them easy to analyze in Excel.

When to Use Nested JSON Mode

Use Nested JSON Mode when your JSON:

Contains nested objects that you want to analyze
Has hierarchical data structures
You want to access nested properties as separate columns
You need to perform calculations on nested values

Example JSON for Nested Mode

json 复制代码

[
  {
    "id": 1,
    "name": "John Doe",
    "contact": {
      "email": "john@example.com",
      "phone": "555-1234",
      "address": {
        "street": "123 Main St",
        "city": "New York",
        "zip": "10001"
      }
    }
  },
  {
    "id": 2,
    "name": "Jane Smith",
    "contact": {
      "email": "jane@example.com",
      "phone": "555-5678",
      "address": {
        "street": "456 Oak Ave",
        "city": "Boston",
        "zip": "02101"
      }
    }
  }
]

Nested Mode Conversion Result (Default Dot Delimiter)

id	name	contact.email	contact.phone	contact.address.street	contact.address.city	contact.address.zip
1	John Doe	john@example.com	555-1234	123 Main St	New York	10001
2	Jane Smith	jane@example.com	555-5678	456 Oak Ave	Boston	02101

Nested Delimiters (Pro Feature)

Nested JSON Mode allows you to customize how nested properties are named using different delimiters:

Dot (.) - Default

contact.email, contact.phone, contact.address.street

Underscore (_)

contact_email, contact_phone, contact_address_street

Double Underscore (__)

contact__email, contact__phone, contact__address__street

Forward Slash (/)

contact/email, contact/phone, contact/address/street

Max Depth Control (Pro Feature)

You can control how deep the converter processes nested objects:

Unlimited Depth (Default)

All nested levels are flattened:

json 复制代码

{
  "level1": {
    "level2": {
      "level3": {
        "value": "deep"
      }
    }
  }
}

Becomes: level1.level2.level3.value

Limited Depth (1-20)

Set a specific depth limit. Objects beyond that depth are converted to strings:

With Max Depth = 2:

json 复制代码

{
  "level1": {
    "level2": {
      "level3": {
        "value": "deep"
      }
    }
  }
}

Becomes: level1.level2 = {"level3":{"value":"deep"}}

Pros of Nested Mode

Better Analysis: Nested data becomes easily analyzable
Excel-Friendly: Leverages Excel's tabular structure
Flexible: Customizable delimiters and depth
Powerful: Handles complex hierarchical data

Cons of Nested Mode

Complexity: More complex than Flat Mode
Long Column Names: Can result in very long column headers
Pro Features Required: Some features require subscription
Learning Curve: Takes time to understand all options

Comparing Flat vs Nested Mode

Side-by-Side Comparison

Let's compare both modes with the same JSON:

Input JSON:

json 复制代码

[
  {
    "id": 1,
    "name": "John",
    "contact": {
      "email": "john@example.com",
      "phone": "555-1234"
    }
  }
]

Flat Mode Result:

id	name	contact
1	John	{"email":"john@example.com","phone":"555-1234"}

Nested Mode Result (Dot Delimiter):

id	name	contact.email	contact.phone
1	John	john@example.com	555-1234

Decision Guide

Scenario	Recommended Mode	Reason
Simple key-value pairs	Flat Mode	No nesting needed
Need to analyze nested data	Nested Mode	Makes nested data accessible
Want to preserve nested structure	Flat Mode	Keeps nested data intact
Have complex hierarchical data	Nested Mode	Flattens for analysis
Quick, simple conversion	Flat Mode	Faster and simpler
Need Excel calculations on nested values	Nested Mode	Values are in separate columns

Practical Examples

Example 1: E-commerce Product Data

JSON:

json 复制代码

[
  {
    "productId": "P001",
    "name": "Laptop",
    "price": 999.99,
    "specs": {
      "cpu": "Intel i7",
      "ram": "16GB",
      "storage": "512GB SSD"
    }
  }
]

Use Nested Mode if you want to:

Filter products by CPU type
Calculate average RAM across products
Create pivot tables by storage type

Use Flat Mode if you want to:

Keep specs as a single field
Store the complete specs as-is
Import into systems that expect simple structures

Example 2: Customer Data with Multiple Levels

JSON:

json 复制代码

[
  {
    "customerId": "C001",
    "name": "John Doe",
    "contact": {
      "email": "john@example.com",
      "phone": "555-1234",
      "address": {
        "street": "123 Main St",
        "city": "New York",
        "state": "NY",
        "zip": "10001"
      }
    }
  }
]

Nested Mode with Max Depth = 2:

customerId	name	contact.email	contact.phone	contact.address
C001	John Doe	john@example.com	555-1234	{"street":"123 Main St","city":"New York","state":"NY","zip":"10001"}

Nested Mode with Unlimited Depth:

customerId	name	contact.email	contact.phone	contact.address.street	contact.address.city	contact.address.state	contact.address.zip
C001	John Doe	john@example.com	555-1234	123 Main St	New York	NY	10001

Example 3: API Response with Mixed Data

JSON:

json 复制代码

[
  {
    "id": 1,
    "title": "Post 1",
    "author": {
      "id": 101,
      "name": "John"
    },
    "tags": ["tech", "programming"],
    "metadata": {
      "views": 1000,
      "likes": 50
    }
  }
]

Nested Mode Result:

id	title	author.id	author.name	tags	metadata.views	metadata.likes
1	Post 1	101	John	["tech","programming"]	1000	50

Note: Arrays like tags are still converted to strings even in Nested Mode.

Tips for Choosing the Right Mode

1. Analyze Your Data Structure

Look at your JSON and identify:

How many levels of nesting exist
Whether you need to analyze nested data
If nested data should be preserved as-is

2. Consider Your Use Case

Think about what you'll do with the Excel data:

Will you need to filter/sort nested values?
Do you need to perform calculations on nested data?
Are you importing into another system?

3. Test Both Modes

When in doubt, try both modes:

Convert with Flat Mode first
Convert with Nested Mode
Compare the results
Choose the one that better fits your needs

4. Use Pro Features Wisely

If you have Pro access:

Experiment with different delimiters
Try different Max Depth settings
Find the combination that works best for your data

Common Pitfalls

Pitfall 1: Using Flat Mode for Complex Data

Problem: You use Flat Mode for deeply nested JSON, then struggle to analyze the data.

Solution: Switch to Nested Mode to flatten the structure.

Pitfall 2: Using Nested Mode for Simple Data

Problem: You use Nested Mode for simple JSON, creating unnecessarily complex column names.

Solution: Use Flat Mode for simple structures.

Pitfall 3: Not Setting Max Depth

Problem: Very deep nesting creates extremely long column names.

Solution: Set an appropriate Max Depth to limit flattening.

Pitfall 4: Wrong Delimiter Choice

Problem: Your chosen delimiter conflicts with your data or naming conventions.

Solution: Choose a delimiter that works with your data and team conventions.

Next Steps

Now that you understand the differences between Flat and Nested JSON conversion modes, you're ready to explore the advanced features available in JSON to Excel. In our next post, we'll cover Pro features and customization options that can take your JSON to Excel conversions to the next level.

Ready to try different conversion modes? Visit the JSON to Excel Web App and experiment with both modes!