🪴 TJ's Notes 1.0

Data Base Management System Lab 1

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Data Base Management System Lab 1

Index

  1. Introduction
  2. Content
  3. References

Introduction

We generated a substantial amount of data, organized it systematically, and then utilized a DBMS for efficient management. This project explores various aspects of DBMS.

Content

Applications

Consistency in DBMS

Rolling Back

Mechanism to revert changes to maintain data integrity.

Parallel Calling

Executing multiple processes simultaneously to improve efficiency.

Constraints

Rules applied to data to maintain accuracy and integrity.

Purpose

Data Redundancy

Reducing duplication of data.

Difficulty in Accessing Data

Improving ease of data retrieval.

Integrity Problems

Ensuring accuracy and consistency of data over its lifecycle.

Atomicity of Updates

Ensuring all parts of a transaction are completed successfully.

Concurrent Access by Multiple Users

Handling simultaneous data access by multiple users without conflicts.

Security Problems

Protecting data from unauthorized access and breaches.

Data Models

Tools

  • Data: Raw information.
  • Data Relationships: Connections between data items.
  • Data Semantics: Meaning and context of data.
  • Data Constraints: Rules and limitations on data.

Relational Model

Explains how to relate two databases together.

Relational Model Example

IDNameDept_NameSalary
101JohnCS70000
102JaneEE80000

Fig 1

Fields

ID, Name, Dept_Name, and Salary are attributes called Fields.

Schema

Defines the structure of the database. For example, the ID field with 5 characters is part of the Schema.

Instances

Specific data at a particular moment in time.

Data Definition Language (DDL)

Specification syntax for defining the database schema. Example:

CREATE TABLE instructor(
    id CHAR(5),
    name VARCHAR(20),
    dept_name VARCHAR(20),
    salary NUMERIC(8,2)
);

DDL Compiler generates table templates stored in the database.

Data Manipulation Language (DML)

Language for accessing and updating data organized by the data model.

  • DML is also known as the query language.
  • Two classes of DML:
    • Pure: For proving computational power and optimization.
    • Commercial: Used in commercial systems, with SQL being the most widely used.

Types of DML

  • Procedural DML
  • Non-Procedural DML

SQL

SQL is a non-procedural query language that inputs multiple tables and returns a single table. It is not Turing machine equivalent.

Database Design

Logical Design

Conceptual framework of the database.

Physical Design

Actual storage of data in the database.

Components

  • Storage Manager
  • Query Processor
  • Transaction Management Component

Applications

Two-Tier Architecture

Client-server architecture with two layers.

Three-Tier Architecture

Client-server architecture with three layers.

Database Users

Naive users ( Expand here )

Enigma

Physical Data Independence

Ability to change the physical schema without affecting the logical schema.

Relevant Information

Rolling Back

Rolling back in a DBMS is a process where the system reverts changes made during a transaction to maintain data integrity in case of an error or failure. This is crucial for ensuring that only valid and accurate data is stored in the database.

Parallel Calling

Parallel calling allows multiple processes to execute simultaneously, enhancing the efficiency and performance of the DBMS. This approach is particularly useful in handling large datasets and complex queries.

Constraints

Constraints are rules applied to the data in a database to ensure data integrity and accuracy. Common types of constraints include primary keys, foreign keys, unique constraints, and check constraints.

Data Redundancy

Data redundancy involves unnecessary duplication of data within a database. Reducing redundancy helps in optimizing storage, improving performance, and maintaining data consistency.

Difficulty in Accessing Data

Improving data retrieval methods within a DBMS can significantly enhance user experience and operational efficiency. Techniques such as indexing and optimized queries are often employed to address this issue.

Integrity Problems

Ensuring the accuracy and consistency of data throughout its lifecycle is critical in a DBMS. Integrity problems can be minimized through the use of constraints, transactions, and proper database design.

Atomicity of Updates

Atomicity ensures that all parts of a transaction are completed successfully; if any part of the transaction fails, the entire transaction is rolled back. This property is one of the ACID (Atomicity, Consistency, Isolation, Durability) principles in DBMS.

Concurrent Access by Multiple Users

Handling concurrent access in a DBMS involves managing multiple users accessing the database simultaneously without causing conflicts. Techniques such as locking, transaction management, and isolation levels are used to manage concurrency.

Security Problems

Protecting data from unauthorized access and breaches is a fundamental aspect of DBMS security. Implementing authentication, authorization, encryption, and auditing measures are essential practices for ensuring data security.

References

  • Date, C. J. (2004). An Introduction to Database Systems. Addison-Wesley.
  • Silberschatz, A., Korth, H. F., & Sudarshan, S. (2010). Database System Concepts. McGraw-Hill.
  • Elmasri, R., & Navathe, S. B. (2015). Fundamentals of Database Systems. Pearson.

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