Why is Error Handling Important in SQL

Error Handling Techniques

1. TRY...CATCH Blocks

2. RAISEERROR Statement

3. Transaction Control

4. Error Codes and Messages

5. Logging Errors

Error Handling in Different Database Management Systems

Understanding Transactions in SQL

1. ACID Principles:

2. Parallelism: SELECT, INSERT, UPDATE, DELETE:

3. Transaction Logs:

Importance of Transactions

1. Improved Reliability:

2. Managing Multiple Users:

3. Resolving Anti-Patterns of Data Updates:

4. Ensuring Proper Error Detection:

5. Safeguard Transactions:

Types of Transactions

1. Implicit Transactions:

2. Explicit Transactions:

What is a Stored Procedure?

What is a Function?

Creating Stored Procedures and Functions

Key Differences Between Stored Procedures and Functions

1. Return Values:

2. Uses In SQL Statements:

3. Side Effects:

4. Transaction Control:

Why the Need to Use Stored Procedures and Functions?

- Reusability:

- Security:

- Performance:

- Consistency:

- Code Organization:

What do you understand about Views?

How to Make a View

CREATE VIEW view_name AS
SELECT column1, column2, ... FROM table_name
WHERE condition;

Kinds of Views

1. Simple Views:

2. Complex Views:

3. Updatable Views:

4. Materialized Views:

Benefits of Using Views

1. Simplification of Complex Queries:

2. Data Security:

3. Enhanced Database Handling:

4. Elimination of Discrepancies:

5. Concealment of Business Logic:

Working With Views

CREATE OR REPLACE VIEW view_name AS SELECT column1 ,column2 ,.... FROM table_name WHERE condition;

Update data via views

Performance rules of thumb

The Importance of Normalization

The Process of Normalization

First Normal Form (1NF)

Second Normal Form (2NF)

Third Normal Form (3NF)

Boyce-Codd Normal Form (BCNF)

Normalization Benefits

1. Decreases Data Duplication:

2. Enhances Data Consistency:

3. Eases Data Administration:

4. Enhanced Speed Benefits:

Problems Needing Attention During Normalization

- N Levels of Amongst Tables Joining:

- Tightening of Performance Criteria:

What are Indexes?

How Indexes Function

Types of Indexes

1. Primary Index:

2. Unique Index:

3. Composite Index:

4. Full-Text Index:

5. Spatial Index:

Creating an Index

Indexes Management

1. Monitoring Index Usage:

2. Rebuilding Indexes:

3. Dropping Indexes:

4. Index Maintenance:

Disadvantages of Using Indexes

- Higher Cost of Storage:

- Increased Time for Data Update:

- Managing Indexes:

What is a Subquery?

Types of Subqueries

1. Scalar Subquery:

2. Row Subquery:

3. Column Subquery:

4. Table Subquery:

The Places that Subqueries Can Be Utilized

- SELECT Clause:

- WHERE Clause:

- FROM Clause:

- INSERT, UPDATE, DELETE Clauses:

Advantages of Using Subqueries

- Modularity:

- Efficiency:

- Flexibility:

Points to Note When Employing Subqueries

- Performance:

- Nested Subqueries:

- Readability:

- Limitations:

Subqueries vs. Joins

What Grouping Means In SQL

Aggregating Data In SQL

- COUNT():

- SUM():

- AVG():

- MAX():

- MIN():

Using Grouping and Aggregating Together

The Role of the HAVING Clause

Real-life Application Grouping and Aggregating

- Total sales per product or region

- Total value of average purchases done by a customer

- Employees that are top sales persons or bottom sales people

- Total sales of each store or each department

- How many orders were made in a period of time

Correct Grouping’s Crucial Role

What Is a Join?

Types of Joins

1. INNER JOIN:

2. LEFT JOIN (or LEFT OUTER JOIN):

3. RIGHT JOIN (or RIGHT OUTER JOIN):

4. FULL JOIN (or FULL OUTER JOIN):

5. CROSS JOIN:

6. SELF JOIN:

Summary of Join Operations in One Paragraph

Understanding Why Joins are Important in SQL

SQL WHERE Clause

The HAVING Clause

Key Differences Between WHERE and HAVING

1. WHEN They Are Used:

2. What They Filter:

3. Compatibility:

Common Use Cases

- Filtering Individual Records (WHERE Clause):

- Filtering Aggregated Data (HAVING Clause):

The Benefits of Using WHERE in Combination with HAVING

Best Practices for WHERE and HAVING

- WHERE Applies to Row Selection and Aggregates:

- Consider Using HAVING for Aggregate Filtering:

- Combine Both Clauses as Required: