Data Modelling for DocFinder
3.1 Data Modelling
Hello guys, this is my fifth blog post for the Internship at Hasura! After choosing the app idea and making prototype/wireframe and setting up local development for the app, the next task to do data modelling for DocFinder.
The links to above posts are given below:
Data modelling is often the first step in database design in which the analysis of data objects and their relationship with other data objects is carried out. It defines how data is connected to each other and how they are processed and stored inside the system.
In this blog I will share the Database schema for my application.
Howeer, there are a dozen of tools available for making of database schema, I have selected DBDesigner.
Here is the image of the Database Schema for the DocFinder App.

Here is a short description for all the tables in the schema.
Doctor Table:
This table contains the name, experience, designation, the info about the days of the week on which the doctor is available. It also contains information about the time, location and specialization of the doctor.
Patient Table:
This table contains the basic information about the patient namely name, age, sex of the patient, This table also contains the information about the health issue of patient. Also there is a column for the preferred time and location the patient has selected.
Location Table:
This table contains the locations to choose from for the patient where the doctor is available.
Specialization Table:
This table contains the specializations of the doctors which are available on DocFinder.
Time Slots Table:
This table contains the time slots available for visit to the doctors on DocFinder.
Manager Table:
This table provides the interlink between the Patients ans the Doctor Table. This table has the appointment location and the time alloted to/selected by patient to meet the doctor.
Coming Up!
In the next blog, I’ll talk about Hasura Data API + Postman collection for my web application Doc Finder.
You can follow me on Twitter here. Thank you for reading. Stay Tuned!!