Oracle Database SQL Certified Associate
1 Introduction to SQL
1-1 Overview of SQL
1-2 History of SQL
1-3 SQL Standards
2 SQL Data Types
2-1 Numeric Data Types
2-2 Character Data Types
2-3 Date and Time Data Types
2-4 Large Object (LOB) Data Types
2-5 Miscellaneous Data Types
3 Creating and Managing Tables
3-1 Creating Tables
3-2 Modifying Tables
3-3 Dropping Tables
3-4 Table Constraints
3-5 Temporary Tables
4 Data Manipulation Language (DML)
4-1 Inserting Data
4-2 Updating Data
4-3 Deleting Data
4-4 Selecting Data
4-5 Using Subqueries
5 Data Control Language (DCL)
5-1 Granting Privileges
5-2 Revoking Privileges
6 Data Definition Language (DDL)
6-1 Creating Tables
6-2 Altering Tables
6-3 Dropping Tables
6-4 Creating Indexes
6-5 Dropping Indexes
6-6 Creating Views
6-7 Dropping Views
7 SQL Functions
7-1 Single-Row Functions
7-2 Aggregate Functions
7-3 Group Functions
7-4 Analytical Functions
8 Joins and Subqueries
8-1 Inner Joins
8-2 Outer Joins
8-3 Self-Joins
8-4 Cross Joins
8-5 Subqueries
9 Set Operators
9-1 UNION
9-2 UNION ALL
9-3 INTERSECT
9-4 MINUS
10 Grouping and Aggregation
10-1 GROUP BY Clause
10-2 HAVING Clause
10-3 ROLLUP and CUBE
10-4 GROUPING SETS
11 Transactions and Concurrency
11-1 Transaction Control Statements
11-2 Locking and Concurrency
11-3 Isolation Levels
12 Oracle SQL Developer
12-1 Overview of Oracle SQL Developer
12-2 Using SQL Worksheet
12-3 Managing Connections
12-4 Running Scripts
13 Advanced SQL Topics
13-1 Recursive Queries
13-2 Model Clause
13-3 PIVOT and UNPIVOT
13-4 Flashback Query
14 Performance Tuning
14-1 Query Optimization
14-2 Indexing Strategies
14-3 Analyzing Query Performance
15 Security and Auditing
15-1 User Management
15-2 Role Management
15-3 Auditing SQL Statements
16 Backup and Recovery
16-1 Backup Strategies
16-2 Recovery Strategies
16-3 Using RMAN
17 Oracle Database Architecture
17-1 Overview of Oracle Database Architecture
17-2 Memory Structures
17-3 Process Structures
17-4 Storage Structures
18 PLSQL Basics
18-1 Introduction to PLSQL
18-2 PLSQL Block Structure
18-3 Variables and Data Types
18-4 Control Structures
18-5 Exception Handling
19 Oracle SQL Certification Exam Preparation
19-1 Exam Objectives
19-2 Sample Questions
19-3 Practice Tests
19-4 Exam Tips
Creating Views in Oracle SQL

Creating Views in Oracle SQL

Key Concepts

Creating views in Oracle SQL involves defining a virtual table based on the result of a SQL query. Views do not store data but provide a way to simplify complex queries, control access to data, and present data in a more user-friendly format. Understanding the following key concepts is essential for effectively creating and using views:

1. CREATE VIEW Statement

The CREATE VIEW statement is used to create a new view. It specifies the view name and the query that defines the view. The view is then treated as a virtual table that can be queried just like a regular table.

2. Simplifying Complex Queries

Views can simplify complex queries by encapsulating the logic in a single object. This allows users to query the view without needing to understand the underlying complexity of the query.

3. Data Security

Views can be used to control access to data by exposing only specific columns or rows. This helps in maintaining data security and privacy by limiting what users can see and modify.

4. Data Abstraction

Views provide a level of abstraction by hiding the underlying table structure. This can be useful when the underlying tables are subject to frequent changes, as the view can remain consistent while the tables evolve.

5. Materialized Views

Materialized views are a special type of view that stores the result of the query physically. This can improve query performance for complex queries that are frequently executed, as the data is precomputed and stored.

Detailed Explanation

1. CREATE VIEW Statement

The basic syntax for the CREATE VIEW statement is:

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

Example: Creating a view named "EmployeeDetails" that selects specific columns from the "Employees" table:

CREATE VIEW EmployeeDetails AS SELECT EmployeeID, FirstName, LastName, HireDate FROM Employees;

2. Simplifying Complex Queries

Views can encapsulate complex queries, making them easier to use. For example, a view can combine data from multiple tables, perform calculations, or filter data based on specific criteria.

Example: Creating a view that combines data from the "Employees" and "Departments" tables:

CREATE VIEW EmployeeDepartment AS SELECT e.EmployeeID, e.FirstName, e.LastName, d.DepartmentName FROM Employees e JOIN Departments d ON e.DepartmentID = d.DepartmentID;

3. Data Security

Views can be used to restrict access to sensitive data. For example, a view can be created to expose only non-sensitive columns, ensuring that users cannot access confidential information.

Example: Creating a view that exposes only the "EmployeeID", "FirstName", and "LastName" columns:

CREATE VIEW PublicEmployeeInfo AS SELECT EmployeeID, FirstName, LastName FROM Employees;

4. Data Abstraction

Views provide a layer of abstraction, allowing users to work with a simplified interface. This is particularly useful when the underlying tables have complex structures or are subject to frequent changes.

Example: Creating a view that abstracts the underlying table structure:

CREATE VIEW EmployeeSummary AS SELECT EmployeeID, FirstName || ' ' || LastName AS FullName, HireDate FROM Employees;

5. Materialized Views

Materialized views store the result of the query physically, improving performance for complex queries. They are particularly useful for queries that are executed frequently and involve large datasets.

Example: Creating a materialized view that stores the result of a complex query:

CREATE MATERIALIZED VIEW EmployeeSales AS SELECT e.EmployeeID, e.FirstName, e.LastName, SUM(s.SalesAmount) AS TotalSales FROM Employees e JOIN Sales s ON e.EmployeeID = s.EmployeeID GROUP BY e.EmployeeID, e.FirstName, e.LastName;

Understanding and mastering these concepts is essential for effectively creating and using views in Oracle SQL. By simplifying complex queries, controlling access to data, providing data abstraction, and leveraging materialized views, you can optimize your database design and improve query performance.