AK TECH CODING

When working with databases, it’s important to organize data in a way that avoids redundancy and improves efficiency. This process is called Normalization . In this post, I’ll explain what normalization is and the different normal forms in simple terms. 1. What is Normalization? Normalization is a process of organizing the data in a database to reduce redundancy and improve data integrity. It involves dividing large tables into smaller, related tables and ensuring that data is stored logically and efficiently. Why is Normalization Important? Without normalization, a database might contain duplicate data, which can lead to data anomalies (inconsistencies) when data is inserted, updated, or deleted. By normalizing your database, you can avoid these issues and make sure the data remains consistent. Example: Let’s say you have a table that stores information about customers and their orders: CustomerID | CustomerName | OrderID | OrderDate -------------------------------------...

When working with databases, you may come across situations where you need to reuse complex queries. In such cases, Views can help simplify your work. In this post, I'll explain what a SQL view is, how to create one, and why it is useful in simple terms. 1. What is a View in SQL? A view in SQL is like a virtual table based on the result of a query. It does not store the data physically. Instead, it shows the data retrieved from one or more tables whenever you access it. You can think of a view as a saved query that you can reuse multiple times. Why Use a View? Views are useful when you have complex queries that are often repeated in your application. They help in: Making your code easier to manage. Improving security by showing only specific columns or rows from a table. Simplifying data retrieval, especially from multiple tables. Example: Here’s a simple example of a view that shows only the customers' names and email addresses from the customers table: ...

When working with large databases, you might notice that retrieving data can sometimes be slow. This is where indexing comes into play. Indexing helps the database find and retrieve data faster, similar to how an index in a book helps you quickly find a topic. In this post, I’ll explain what indexing is and the different types of indexes in simple terms. 1. What is Indexing? An index in a database is like a roadmap that helps you find specific information faster. Instead of scanning the entire table, the database can use the index to quickly locate the row you're looking for. It improves the performance of queries, especially those with SELECT , WHERE , or JOIN clauses. Why is Indexing Important? Without an index, the database has to scan every row in a table to find what it’s looking for. This process is called a "full table scan," and it can be slow, especially in large databases. Indexing speeds up this process by narrowing down the search area. Example: --...

When working with databases, understanding key constraints is essential for ensuring data integrity. In this post, I’ll explain what a PRIMARY KEY is, how it differs from a UNIQUE KEY , and when to use them. 1. What is a PRIMARY KEY? A PRIMARY KEY is a column (or a set of columns) in a table that uniquely identifies each row. It ensures that no two rows have the same primary key value and that the key value is not null. Key Characteristics of PRIMARY KEY: Uniquely identifies each row in a table. Cannot contain NULL values. A table can only have one PRIMARY KEY . Example: -- Defining a PRIMARY KEY on 'customer_id' CREATE TABLE customers ( customer_id INT PRIMARY KEY, name VARCHAR(100), email VARCHAR(100) ); 2. What is a UNIQUE KEY? A UNIQUE KEY constraint also ensures that all values in a column (or a set of columns) are unique. However, unlike the primary key, a unique key can contain NULL values, and a table can have multiple unique keys....

When working with databases, SQL query performance is crucial. A slow query can make your application sluggish and affect the overall user experience. In this post, I’ll explain how to optimize SQL queries with simple tips that anyone can understand! 1. Use SELECT Fields Instead of SELECT * It’s tempting to use SELECT * to grab all the data from a table, but this can slow down your query, especially if the table has a lot of columns. Instead, only select the columns you need. Example: -- Avoid this SELECT * FROM customers; -- Do this SELECT name, email FROM customers; 2. Use WHERE Clauses to Filter Data Always use a WHERE clause to filter data and reduce the number of rows the database has to process. This can make a huge difference, especially when dealing with large tables. Example: -- Without filtering SELECT * FROM orders; -- With filtering SELECT * FROM orders WHERE status = 'Shipped'; 3. Avoid Using Functions in WHERE Clauses Using functions in a WHERE ...

When working with databases, you often need to get information from more than one table. This is where joins come in! Joins allow you to combine rows from two or more tables based on a common column between them. In this blog, I’ll explain what joins are and go over the main types with simple examples.

Introduction When working with a database, you often need to store text, such as names, addresses, or descriptions. SQL offers different types of text storage: CHAR , VARCHAR , NCHAR , and NVARCHAR . Although they all store text, they differ in how they store and handle data. Understanding these differences can help you make the right choice and optimize your database.

When working with SQL, two common types of subprograms you’ll come across are Functions and Procedures . Both are used to perform specific tasks and encapsulate SQL code, but they serve different purposes and have important differences. Let's explore these in detail to help you understand when and why you would use each.