A Data Model in Database Management System (DBMS), is the concept of tools that are developed to summarize the description of the database.
It is classified into 3 types:
1. Conceptual Data Model :
Conceptual data model, describes the database at a very high level and is useful to understand the needs or requirements of the database. It is this model, that is used in the requirement gathering process i.e., before the Database Designers start making a particular database. One such popular model is the entity/relationship model (ER model). The E/R model specializes in entities, relationships and even attributes which are used by the database designers. In terms of this concept, a discussion can be made even with non-computer science(non-technical) users and stakeholders, and their requirements can be understood.
2. Representational Data Model :
This type of data model is used to represent only the logical part of the database and does not represent the physical structure of the databases. The representational data model allows us to focus primarily, on the design part of the database. A popular representational model is Relational model.
3. Physical Data Model :
Ultimately, all data in a database is stored physically on a secondary storage device such as discs and tapes. This is stored in the form of files, records and certain other data structures. It has all the information of the format in which the files are present and the structure of the databases, presence of external data structures and their relation to each other.
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- Data Replication in DBMS
- Building a Data Warehouse in DBMS
- Data Objects, Attributes and Relationships in DBMS
- Difference between Row oriented and Column oriented data stores in DBMS
- OSI, TCP/IP and Hybrid models
- Designing models in Cassandra
- Database Recovery Models
- Thread Models in Operating System
- Characteristics of Biological Data (Genome Data Management)
- Difference between Data Warehousing and Data Mining
- Difference between Data Privacy and Data Protection
- Difference between Data Warehouse and Data Mart
- Difference between Data Privacy and Data Security
- Difference between Data Lake and Data Warehouse
- Types of Sources of Data in Data Mining
- Data Architecture Design and Data Management
- Data Mining: Data Warehouse Process
- Data Mining: Data Attributes and Quality
- Data Reduction in Data Mining
- Data Abstraction and Data Independence
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