Contents

1. Database Management System

1. Database and Database Users

2. Database Users

3. File Processing System

4. Database Management Systems

5. Database Schema and Instances

6. Data Abstraction

7. Data Independence

8. Centralized and Client Server Architecture of DBMS

8.1 Centralized Database Systems

8.2 Client-Server Systems

2. Data Models

1. Data Models

2. ER Model for Conceptual Design

3. Mapping Cardinalities

4. Types of Keys

5. ER – Diagram

3. Relational Model

1. RELATIONAL DATA MODEL

2. Relational Algebra

3. SQL- A Relational Database Language

4. Indexing

5. Views

6. Security in SQL

7. Triggers

4. Relational Database Design

1. Introduction

2. Functional Dependencies

3. Undesirable Properties of a Bad Database Design

4. E.F. Codd’s Rules

5. Steps followed by Application Developer to Design Application Scheme

6. Normalization Process

7. Advantages and Disadvantages of Normalization

8. Denormalisation

9. Loseless Joins

10. Decompositions

5. Transaction and Concurrency Control

1. Concept of Transaction

2. Properties of Transaction

3. State of Transaction

4. Implementation of Atomicity and Durability

5. Concurrent Executions

6. Concurrency Control Techniques

7. Concurrency control

6. Crash Recovery and Backup

1. Why Recovery is Needed?

2. Storage Structure

3. Recovery and Atomicity

4. Failure with loss of Non-volatile Storage

5. Recovery from Catastrophic Failure

6. Remote Backup Systems

7. Security and Privacy

1. Introduction

2. Database Security and the DBA

3. Discretionary Access Control Method

4. Mandatory access control method

5. Uses of Views in Security Enforcement

6. Overview of Encryption Technique for Database

7. Statistical Database Security

8. Data Warehousing and Data Mining

1. What is a Data Warehouse?

2. Data Warehousing with Materialized Views

3. Understanding the Framework of the Data Warehouse

4. Data Warehouse Options

5. Type of End-user

6. Developing Data Warehouses

7. Avoiding Warehouse Failures

8. Data Mining

9. Difference between Data Mining and Normal Query