API Testing Isn’t Just for Developers: Here’s Why Data Analysts Need It Too.

Hello Everyone,

I am very glad to connect with you all once again through this Blog. Yes from the title you would have got an idea about what am gonna write about it. The term "API TESTING" is very familiar topic among all tech backgrounds. But am very surprised and wondered how it would help a Data Analyst as a secret weapon to find smarter insights. So I would like to share my journey with API Testing and the versatile POSTMAN tool and its capabilities in this blog. Let's Start......

WHAT IS API TESTING?

"API" is abbreviated as Application Program Interface. Yes as per the name defines it is the interface between two Application layers which is a Server and Client Application. This API's helps Server and Client application to communicate each other back and forth in order to send and receive any kind of data in simple words.

For Example, Consider we have a Front end Application (any web application's User Interface) as a client and a Back end Application (any database server) as a server end. Now Client end needs to communicate with the Server to fetch some data, So it would get help from any API's in between them which is developed by a developer.

This is called the three tier web application concept.

TYPES OF API:

Generally we have Two types of API's.

1. SOAP API (Legacy approach) - Simple Object Access Protocol. It uses only the XML to encode Request and Responses.

2. REST API (Latest Approach) - Representational State Transfer. A REST API is a way for different software systems to communicate over the web using HTTP methods. It allows to send requests and get back structured data, usually in JSON or XML format.

   So this REST API is the Latest one which is majorly used among Software development in testing. We will learn a little more detail in it.

   The REST API is a structured one. It basically needs the following details to fetch data as a Request Payload,

   URL with EndPoints.

   HTTP Methods (Post, Get, Put and Delete for CRUD Operation)

   Headers (Authorization Token Keys)

   Params (Parameters passed in url)

   Body (Only required for Put and Post request).

   In Response Payload you will have the following details:

   Status Code

   Status String message

   Data in JSON format

   Headers

   Here we should have better understanding in some terminologies.

   TERMINOLOGY REQUIRED:

   1. Base URL & EndPoint - The URL comes with the Endpoint to be checked. It is attached with the base url. In general the development team has to provide the endpoints with the Contract Document.

   2. Payload - Generally the Data in JSON format which is given in the Body as Request and returned as a Response is called Payload. (Request Payload & Response Payload)

   3. Status Code - While checking the API you will get Response Payload with some Status Code which says what is the action has been made whether it is successful or not.

   
   

   Some Example Status Codes are :

   
   
   
   

Code	Meaning	Description
200 OK	Success	Request completed successfully
201	Created	New resource created
400	Bad Request	Request is invalid or missing parameters
401	Unauthorized	Invalid or missing authentication
404	Not Found	Resource does not exist
500	Internal Server Error	Problem on the server side

So whenever you get a chance to work with an API you should thoroughly explore the Functionality, Limitations and the Purpose of the API from the API COntract Document. This Contract Document will be given by the Development Team.

Different REST API Tools are:

Graphical User Interface (GUI)-based Tools

These are beginner-friendly and great for manual and exploratory API testing.

1. Postman – Most widely used tool for API testing and automation, supports collections, scripting, environment variables, and mocking.

2. Swagger UI / SwaggerHub – Used for testing APIs directly from OpenAPI (Swagger) documentation.

Automated Testing Frameworks and Libraries

For continuous integration (CI), scripting, and automated tests.

1. REST Assured (Java) – Library for testing REST services in Java, widely used in backend testing.

2. Pytest + requests (Python) – Popular combo for lightweight and scalable API test automation.

3. JMeter – Originally a load testing tool, but supports API testing via HTTP Request samplers.

CI/CD & DevOps Integrated Tools

For API testing in deployment pipelines.

1. Newman (Postman CLI) – Run Postman collections in CI/CD pipelines.

So I have an opportunity to work with Beginner Friendly POSTMAN Work Space. It has been given me another perspective of Collecting data from various API's , Websites.

Why it is very much Important in Data Analyst Life :

• Allows real-time data access from online platforms (e.g., sales data, stock prices, weather).

• Helps in automating data pulls from different tools (e.g., CRMs, databases).

• Integrates well with tools like Postman, Python, Power BI, and Tableau.

As a data analyst, working with real-time data is essential for creating dynamic and up-to-date dashboards. Postman, a powerful API testing and development tool, allows analysts to interact with REST APIs and fetch live data from various sources such as web services, CRMs, analytics tools, or custom applications.

The process begins by using Postman to configure and send HTTP requests (like GET, POST) to the desired API endpoint. For example, an analyst might connect to a financial data provider or a CRM system via their REST API. Once the request is made, Postman receives the response in structured formats like JSON or XML.

Using Postman’s features, the analyst can:

1. Inspect and test API responses,

2. Set up variables and environments,

3. Save collections of API calls for reuse.

After validating the API responses, the data can be exported from Postman in JSON format or used directly through Postman’s built-in scripting (Pre-request Script / Tests) to automate repetitive tasks.

To integrate this data into a dashboard tool like Power BI, Tableau, or Excel, the analyst can:

• Use Power BI’s Web connector to call the same API endpoint,

• Or use Python scripts with requests library, replicating the logic from Postman to pull data in real time,

• Or schedule a script that calls the API, parses the JSON data, and pushes it to a database or spreadsheet which the dashboard reads from.

This flow bridges API data and business intelligence tools, enabling analysts to visualize KPIs and trends in real time without manual data entry. Thus, Postman serves not only as a testing tool but also as a stepping stone for seamless data automation and integration.

CONCLUSION:

Yes, I always had a passion to work with Real time Data. When you have a Scheduled Refresh Environment and Producing Insights like a Hot hot Newspaper coming out from a printing machine it gives you an immense pleasure and confident on your work. I Hope, I delivered my experience in a way so that it will help another Analyst to Dig deeper in API's to fetch more real time data to reduce Manual entry or bored working with sheets for the Long time, even the one who is afraid to step into this feature can confidentially go a step ahead.

Thank You!