JSON 101: The Language of Data in the Modern Web

Imagine you’re using a weather app, sending a message, or ordering a pizza online. Behind the scenes, all these apps are talking to servers, asking for data, and presenting it to you instantly. But how do they understand each other? The answer, more often than not, is JSON.

JSON (JavaScript Object Notation) is the most widely used data format for exchanging information between systems—especially in web and mobile applications. Whether it’s front-end JavaScript fetching content from a server or a Python script connecting to a third-party API, JSON is likely the format delivering the goods.

Why JSON? Because it’s lightweight, easy to read, and supported by almost every modern programming language. It’s become the common language of the internet, and understanding how it works is a must for developers, analysts, and anyone working with data.

What Is JSON?

JSON stands for JavaScript Object Notation. At its core, it’s a text-based format derived from JavaScript, used to represent structured data. But don’t be fooled by the name—it’s not just for JavaScript developers.

JSON became popular because it combines simplicity with power. Unlike older formats like XML, JSON is easier to read, write, and parse. It was first introduced in the early 2000s and quickly gained traction with the rise of AJAX (Asynchronous JavaScript and XML)—which ironically dropped XML in favor of JSON.

Here’s a simple way to think about it: JSON lets computers talk to each other using a format that humans can also understand. And that’s a big deal when you’re debugging data, designing APIs, or building scalable applications.

Anatomy of JSON

JSON is built on two basic structures:

• Objects (collections of key-value pairs)
• Arrays (ordered lists of values)

Each JSON file or string is made up of these elements, along with basic data types like strings, numbers, booleans (true or false), null, and nested combinations of objects or arrays.

Here’s a simple example:

{ "name": "Taylor", "age": 28, "isStudent": false, "skills": ["JavaScript", "Python", "SQL"], "address": { "city": "San Diego", "zip": "92101" } }

Let’s break it down:

• "name" and "age" are keys paired with values.
• "skills" is an array (a list of strings).
• "address" is another object inside the main object—a nested structure.

This type of nested, hierarchical formatting is what makes JSON so powerful and flexible for representing complex data in a clean, compact way.

Common Use Cases

JSON is used everywhere. If you’re working with web services, REST APIs, or modern front-end frameworks like React or Angular, you’ll run into JSON constantly. Some of the most common uses include:

• APIs: JSON is the standard for sending data between clients (like a browser) and servers. Whether you’re fetching product details from an e-commerce API or posting data to a social media platform, you’re likely sending/receiving JSON.
• Configuration Files: Tools and libraries often use .json files for settings. For example, package.json in Node.js projects defines dependencies and scripts.
• Databases: NoSQL databases like MongoDB use JSON-like formats (BSON) to store data, making them schema-flexible and ideal for modern apps.
• Mobile Apps: Android and iOS apps consume JSON from servers to update content on the fly—like loading new tweets or updating your stock watchlist.

JSON’s ability to represent anything from a simple message to a fully nested data model makes it a perfect choice for dynamic applications.

Working With JSON

The beauty of JSON is how easily it integrates with nearly every programming language.

In JavaScript, it’s built right in:

const jsonString = '{"name": "Taylor", "age": 28}'; const user = JSON.parse(jsonString); console.log(user.name); // Taylor

And you can go the other way too:

const obj = { name: "Taylor", age: 28 }; const json = JSON.stringify(obj);

In Python, the json module handles reading and writing:

import json json_string = '{"name": "Taylor", "age": 28}' data = json.loads(json_string) print(data['name']) # Taylor # Converting back json_out = json.dumps(data)

There are also tools to make working with JSON easier:

• Postman for testing APIs
• VS Code with JSON plugins for formatting
• Browser DevTools to inspect network requests and see JSON responses

Being able to read and manipulate JSON is a core skill for any tech-savvy professional today.

Best Practices and Gotchas

While JSON is simple, it’s not entirely foolproof. Here are a few common mistakes and tips:

• Trailing Commas Are Invalid: Unlike JavaScript arrays/objects, JSON does not allow a comma after the last item. This will cause a parsing error.
• Keys Must Be Strings: All keys in JSON objects must be enclosed in double quotes. No exceptions.
• Case Sensitivity: JSON keys are case-sensitive. "Name" and "name" are two different keys.
• Keep It Consistent: Use clear, consistent naming conventions. Avoid mixing formats like firstName, first_name, and Firstname.
• Security Tip: Never blindly trust JSON from unverified sources. Malformed or malicious JSON can lead to injection attacks if handled improperly.

By following these best practices, you’ll ensure your JSON stays clean, safe, and compatible with various tools and systems.

JSON in Power Automate: The Backbone of Flow Logic

If you’ve spent time building flows in Power Automate, you’ve probably already encountered JSON—even if you didn’t realize it. JSON is at the core of how data is structured, passed, and manipulated within flows. From triggering events to parsing API responses, JSON plays a pivotal role in making your flows smart, dynamic, and scalable.

Dynamic Content and JSON Behind the Scenes

Whenever you add a trigger or action in Power Automate—say, “When an item is created in SharePoint”—the platform retrieves a JSON schema behind the scenes to define what fields and values are available. This schema is what powers the Dynamic Content pane, allowing you to reference fields like “Title” or “Created By” with just a click.

But under the hood? It’s a JSON object being passed from one step to the next.

The Parse JSON Action

One of the most powerful tools in Power Automate is the "Parse JSON" action. This action allows you to take raw JSON data—often from an HTTP request, Power App, or custom connector—and break it into structured content you can work with downstream.

For example, let’s say you make an HTTP request to an API that returns:

{ "user": { "name": "Taylor", "email": "taylor@example.com" }, "status": "active" }

To access user.name or status in later steps, you’d use the Parse JSON action with a defined schema so Power Automate knows what to expect.

Generating Schemas Automatically

Power Automate helps you by offering a “Use sample payload to generate schema” option. You can paste in a sample JSON object, and it will automatically build a schema for parsing—no guesswork needed. This speeds up development and reduces errors when handling complex or deeply nested JSON.

Custom Expressions with JSON Functions

Power Automate also includes a suite of JSON-related functions for fine-tuning data:

• json(): Converts a string to a JSON object.
• string(): Converts a JSON value to a string.
• outputs() and body(): Retrieve specific portions of JSON content from earlier actions.

Want to grab a nested value from a parsed output? You might use an expression like:

body('Parse_JSON')?['user']?['email']

These expressions let you surgically extract exactly what you need from a large blob of JSON.

Sending JSON Payloads to APIs

If your flow needs to call an external API using the HTTP action, chances are you’ll be building a custom JSON payload in the body. Power Automate supports this natively using the "Raw" mode of the HTTP action, letting you define the structure of the request you’re sending:

{ "id": "12345", "message": "Triggered from Power Automate" }

Getting comfortable with writing and reading these structures unlocks integrations with countless systems and services.

Mastering JSON = Mastering Power Automate

The more you work with Power Automate, the more you’ll see how crucial JSON is. Whether you’re parsing API responses, handling inputs from Power Apps, or customizing advanced expressions, your success often depends on understanding JSON.

The good news? You don’t have to memorize everything. Just being comfortable with how JSON works, what a schema looks like, and how to extract values will make your flows more reliable, powerful, and maintainable.

JSON Is Simple, But Powerful

JSON is one of the foundational skills of modern development. Whether you’re building apps, testing APIs, or configuring tools, understanding how JSON works will save you time and headaches.

The best part? You don’t need to be a full-stack developer to understand JSON. It’s a universal format that anyone in tech—from product managers to QA testers—can benefit from learning. If you’re just getting started, keep exploring sample files, play with APIs, and try creating your own JSON structures.

Once you’re comfortable with JSON, you’ll find it opens doors to understanding APIs, cloud services, database design, and even AI/ML data pipelines. It’s a small skill with a massive impact.

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