Data Engineering

Data Modeling — High Level Overview

Vasanthan R's photo
Vasanthan R
·

3 min read

You must have heard often nowadays that data is the new oil but if it is not organized or structured properly it will remain as crude oil making it unusable to get anything out of it.Whether you are going to build an app for ride share or a food delivery platform or a social media platform a well designed data model ensures efficiency,scalability and a seamless user experience.

What is Data Modeling?

Data modeling basically refers to to process of defining how the data is stored, accessed and related within a system.To ensure. The databases meets the business and technical requirements, data modelling provides a blueprint for databases

Types of Data Models

There are 3 major types of data models widely used in various applications.

  1. Conceptual model — This model focuses more on the high level design based on business concepts and relationships.
  2. Logical model — This model is more detailed specifying attributes, entities and relationships.
  3. Physical model — This model literally defines how the data is stored in our system.

Real-Life Examples of Data Modeling

Let’s take three well-known platforms and break down their data models.

  1. Uber: Connecting Riders and Drivers

Uber needs a robust data model to handle millions of real-time ride requests. Here’s how it might look

Entities:

• Users (Riders, Drivers)

• Trips (Trip details, Pricing, Status)

• Vehicles (Car type, Availability)

• Payments (Fare, Discounts, Transactions)

Key Relationships:

• A User can request multiple Trips.

• A Trip is assigned to one Driver but can have multiple Payment Methods.

This relational model ensures quick matching between riders and drivers, dynamic pricing, and secure transactions.

2. Zomato: Managing Restaurants & Orders

Zomato’s data model needs to manage restaurants, customers, orders, and reviews.

Entities:

• Users (Customers, Restaurant Owners)

• Restaurants (Cuisine, Location, Ratings)

• Orders (Items, Delivery Status, Payment)

• Reviews (Ratings, Comments)

Key Relationships:

• A User can place multiple Orders.

• A Restaurant can have many Reviews from different Users.

• Each Order is linked to a Restaurant and a User.

This model ensures that Zomato can fetch restaurants based on user preferences, show real-time order tracking, and enable smooth payments.

3. Instagram: Social Media at Scale

Instagram’s success depends on a well-structured database that efficiently handles millions of posts, likes, and followers.

Entities:

• Users (Name, Bio, Followers)

• Posts (Images, Captions, Hashtags)

• Likes (Who liked what)

• Comments (Text, User, Timestamp)

Key Relationships:

• A User can have multiple Followers.

• A Post can have many Likes and Comments.

• A User can create multiple Posts.

Instagram’s data model ensures fast loading times, optimized feed ranking, and personalized recommendations.

Why Data Modeling Matters?

  • Performance optimization
  • Scalability
  • Data Integrity
  • Security and Compliance

Conclusion

So next time you order food or book a cab ride or scroll through instagram remind yourselves that a strong data model is the reason behind your seamless experience on these apps.

Whether you are a developer, data analyst or data engineer or just a tech enthusiast mastering the data modeling concepts can be a game changer in this data driven world.

What are your thoughts on data modeling?List any interesting activities or concepts that came up during your data modeling in the comments.Lets discuss and share our knowledge.