How to Create Dataset from JSON?

  

Mark Regan
Published: July 30th, 2025 • 5 Min Read

JSON(JavaScript Object Notation) is one of the most commonly used files for exchanging and storing data. It is a lightweight, human readable and flexible file to store data structure for web applications, API’s and backend systems. So, it’s crucial to create a dataset from JSON by manually and using Expert Verified Approach.

But working with JSON only isn’t ideal for data analysis, machine learning and repointing purposes. These tasks often require raw JSON files in structure format that tools like python(pandas), R, SQL Engines or big data framework can understand.
Creating a dataset from JSON means needed to convert a JSON file into tabular or structured format(e.g., SQL, or CSV file. This process often contain:

• Reading or storing data from a JSON file.
• Parsing or flatting nested structure database.
• Inferring or specifying a schema.
• Storing or exporting the result in a usable dataset format.

When you’re building a dashboard, training models or integrated data pipelines, being able to create a dataset from JSON is a functional skill that bridges unstructured data with structured analysis.

Why use JSON to Create Datasets?

• Most Restful API returns data in JSON format by default. If you’re pulling data from third party services such as Twitter API, Firebase, OpenAI) you’re almost certainly working with JSON. Converting this data into a dataset is essential for analysis.
• JSON supports nested structure(array and objects) and it’s easy to read and write. This makes it ideal for complex data relationships like client records, product list or event details.
• JSON is supported almost evert programing language such as C#, Python, Java, JavaScript and more. This makes it highly portable when creating datasets in different environments.
• While traditional tabular formats like CSV required flat data, JSON file allows for semi-structured data(e.g., nested list and objects). This makes it more versatile when working with real-world data that doesn’t fit properly in rows and columns.

Premier Attributes of Recommended Software

• It supports dual mode to select files or whole folders to convert JSON files.
• This software offers a simple initiative interface to make it a reliable tool for all beginner and professional users.
• You can also convert JSON to Readable format to easily understand the content available in the JSON file.
• With this wizard, you will get 25+ saving options to easily export JSON data and make a more flexible dataset.
• This software allows you to convert individual or batch JSON files without facing any limitations.

Also Read: What is a Dataset in Machine Learning?

How to Create Datasets from JSON Manually?

1. Check JSON file data such as user id, name, email, user id-2, name, email, as available.
2. Now Open SQL Database or MYSQL Database and enter command create table users(id primary key, name Varchar(100), email VARCHAR(100));
3. For nested JSON where you need multiple tables(“id”:1, “name”:”Alice”, “orders”:[{“order_id”:101, “amount”:200}, {“order_id”:102, “amount”:150}]}.
4. CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(100), Create Table orders(order_id INT PRIMARY KEY, user_id INT, amount DECIMAL, FOREIGN KEY(user_id)REFERENCES user(id));
5. Insert values into users(id INT PRIMARY KEY, name VARCHAR(100);
6. Create Table orders(order_id INT PRIMARY KEY, user_id INT, amount DECIMAL, FOREIGN KEY(user_id) REFERENCES user(id));
7. Insert values into users(id, name, email) values(1, Alice, ‘[email protected]’, ), (2, ‘Bob’,’[email protected]’);
8. For nested data: INSERT INTO orders(order_id, user_id, amount)VALUES(101, 1, 200),(102, 1, 150);

Boundaries of Manual Method

• Manually writing SQL queries and insert values is not reliable to perform by all and also increases the chances of syntax error or missing values.
• It’s not workable for large datasets. A JSON file with hundreds or thousands of records would take too long to convert by hand.
• Complex or deeply nested JSON(e.g., array within Objects) requires creating multiple related tables which is not simple to manage and maintain manually.
• Manually conversion doesn’t detect datatypes or null values as needed. You must define every data by yourself and it will take lots of time to set up.

Wrap Up

In this guide, we have shared all possible methods to create a dataset from a JSON file. As manual approach required deep technical skills and users must be friendly with databases to handle this approach. So, we recommend you to choose Expert Recommended Software as it can easily handle any number of JSON files and is also a reliable tool to easily extract data from JSON files and offers 25+ saving options to make it more flexible and export as per user requirement.