In a relational database management system (RDBMS), there are several bad practices and database blunders what you must avoid in RDBMS and why for optimal performance and data integrity:
Common RDBMS Pitfalls – Database Blunders
1-Avoiding Unnormalized Data – Storing redundant data or not normalizing your database can lead to data inconsistencies, increased storage requirements, and difficulties in maintaining data integrity.
Example: Consider a database for a library. Instead of having a separate table for authors and storing author details in each book entry, normalize the data. Create an “Authors” table with author information and establish a relationship with the “Books” table using author IDs. This prevents redundant author data and ensures consistency.
Real Life Example: Consider an e-commerce platform where product details are duplicated in every order. If the product information changes, updating each order becomes cumbersome. Normalizing the data by having a separate “Products” table avoids redundancy.
Consequence of Not Following: Without normalization, a change in product details would require updating every order record, leading to data inconsistency and increased maintenance efforts.
Bad Way:
-- Storing redundant author information in every book entry
CREATE TABLE Books (
BookID INT PRIMARY KEY,
Title VARCHAR(255),
AuthorName VARCHAR(255),
Genre VARCHAR(50)
);
Good Way:
-- Normalizing data with a separate Authors table
CREATE TABLE Authors (
AuthorID INT PRIMARY KEY,
AuthorName VARCHAR(255),
Bio TEXT
);
CREATE TABLE Books (
BookID INT PRIMARY KEY,
Title VARCHAR(255),
AuthorID INT,
Genre VARCHAR(50),
FOREIGN KEY (AuthorID) REFERENCES Authors(AuthorID)
);
For detailed information follow this link: Why Avoiding Unnormalized Data is Crucial in RDBMS? Top 8 Bad Practice We Must Stop Doing.
