In SQL interviews, one of the most frequently asked questions is about data normalization. Data normalization involves reorganizing data across multiple tables to minimize data redundancies and duplicates. The process helps in establishing logical relationships between data tables. For example, on platforms like Amazon, user information such as ID, name, email, and phone number is stored in one table, while purchase details and shipping information are organized into separate tables. The essence of normalization is to efficiently manage and connect data across different tables.
Highlights
Normalization is about reorganizing data to minimize redundancy 📉.
It involves creating logical relationships between different tables 🔄.
User info and product info are stored in separate tables on e-commerce sites like Amazon 🛍️.
Key Takeaways
Data normalization helps reduce redundancy by organizing data across multiple tables 📊.
Logical relationships are established between tables through normalization 🔗.
User data and purchase details are often stored separately for efficiency, like on Amazon 🛒.
Overview
In SQL interviews, understanding data normalization is crucial. It’s all about ensuring that the data in your database is organized efficiently to reduce redundancies and improve data integrity. Instead of lumping everything into a single table, data is spread across multiple tables in a structured way.
Imagine browsing an online store like Amazon. Your personal information is stored separately from your product purchases. This method of data organization is called normalization. It helps store data logically and efficiently, making data management simpler and more effective.
The ultimate goal of normalization is to reduce data duplication and ensure a clean database structure. By doing so, you connect different but related pieces of data, creating a comprehensive data network that is both accessible and maintainable. This is why SQL professionals are often probed about normalization in interviews.
Most asked in SQL Interviews #sql Transcription
00:00 - 00:30 most as SQL interview question is what is data normalization so in a very simple node data novelization can be called as reorganizing the data across multiple tables so you are trying to reorganize the data across multiple tables why you are reorganizing the data is in order to reduce the data redundancies so whatever the data you feel it confusing or there is a duplicate related data is available then saying a duplicate the same data is repeated multiple times or so we are
00:30 - 01:00 trying to reorganize the data across multiple tables and we are connecting them with a specific logical relationships we call it as data normalization so one such example of data normalization is we whenever we are going to an Amazon all our data going to be stored like user ID like name email ID phone number into one table and all the different products you are buying into another table all the kind of products which are shipped into another table so this is called as data normalization and there are different types of forms