Data-Models-in-DBMS-An-Overview.pptx.pptx

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1. PRESENTATION on Discussion about the different Data Models in DBMS Database management System,(PCC-CS601) Submitted by Name – Shibadipta Pal Dept – CSE Semester – 6 th Year – 3 rd Roll – 10200123064 Department of Computer Science and Engineering KALYANI GOVT. ENGG. COLLEGE

2. Introduction Defining Structure A blueprint for organizing data within a database, defining its structure and relationships between elements. Relationships Describes how different data elements relate to each other, enabling effective retrieval and manipulation of information.

3. The Hierarchical Data Model Tree Structure Organizes data in a hierarchical tree structure, with parent-child relationships between elements. Top-Down Approach Data is accessed in a top-down approach, starting from the root node and traversing down the branches. Examples Used in early database systems, such as IMS (Information Management System) and some legacy systems.

4. The Network Data Model 1 Extends Hierarchy Extends the hierarchical model by allowing multiple parent-child relationships between elements. 2 Data Sharing Provides better data sharing and flexibility compared to the hierarchical model. 3 Complexity Can become complex to manage due to the intricate relationships and connections between data elements.

5. The Relational Data Model Tables and Relations Organizes data into tables, with each table representing a distinct entity, such as Customers or Products. Structured Data Uses structured data stored in tables, with rows representing records and columns representing attributes. Foreign Keys Relates tables using foreign keys, which reference primary keys in other tables, establishing relationships between entities.

6. The Entity-Relationship (ER) Model 1 Visual Representation Provides a visual representation of data entities and their relationships using diagrams. 2 Designing Databases Used as a design tool to model data before implementing a database system. 3 Understanding Relationships Helps understand the structure of data and how different entities interact within the database.

7. Object-Oriented Data Model Data and Behavior Combines data and behavior (methods) within objects, representing real-world entities. Inheritance and Polymorphism Supports inheritance, allowing objects to inherit properties and methods from parent classes. Encapsulation Encapsulates data and methods within objects, protecting internal data and providing controlled access.

8. NoSQL Data Models Flexibility Offers greater flexibility in data structures, supporting semi-structured and unstructured data formats. 1 Scalability Designed for handling massive datasets and high-volume data operations. 2 Big Data Well-suited for handling big data, where relational models may become too complex. 3

9. Semi-Structured Data Model A flexible approach that allows for both structured and unstructured data. It uses tags or key-value pairs to organize data elements. 1 JSON Commonly used for data exchange and API communication. 2 XML Offers a hierarchical structure for representing data, often used for document storage and web services. 3 YAML A human-readable format known for its simplicity and clarity.

10. Conclusion: Choosing the Right Model 1 Data Structure Consider the type and complexity of your data. 2 Performance Evaluate the performance requirements of your database. 3 Scalability Determine the scalability needs for your data storage and retrieval.

11. Bibliography and References An Introduction to Database Systems C.J. Date Database Design (2nd Edition) Adrienne Watt Conceptual Data Modeling and Database Design: A Fully Algorithmic Approach Cristian Mancas

12. THANK YOU