view of data dbms
TRANSCRIPT
Rahul Narang
140950107045
CSE A
Semester3
DBMS(ALA)
Topic : VIEW OF DATA
DATA ABSTRACTION
INSTANCES & SCHEMAS
DATA MODELS
DATA ABSTRACTION
DATA ABSTRACTION
Physical Level
Logical Level
View Level
The lowest level of abstraction describes how a system actually stores data.
The physical level describes complex low-level data structures in detail.
The next higher level of abstraction describes what data the database stores, and what relationships exist among
those data. The logical level thus describes an entire database in terms of a small number of relatively simple
structures. Although implementation of the simple structures at the logical level may involve complex
physical level structures, the user of the logical level does not need to be aware of this complexity. This referred to
as physical data independence. Database administrators, who must decide what information to keep in a database,
use the logical level of abstraction.
The highest level of abstraction describes only part of the entire database. Even though the logical level
uses simpler structures, complexity remains because of the variety of information stored in a large
database. Many users of a database system do not need all this information; instead, they need to
access only a part of the database. The view level of abstraction exists to simplify their interaction with
the system. The system may provide many views for the same database.
INSTANCES &SCHEMAS
The environment of database is said to be instance. A database instance or an ‘instance’ is made up of
the background processes needed by the database software. These processes usually include a process monitor, session monitor, lock monitor, etc. They will vary from database vendor to database vendor.
A database instance (Server) is a set of memory structure and background processes that access a set
of database files.
A database schema of a database system is its structure described in a formal
language supported by the database management system (DBMS) and refers to
the organization of data as a blueprint of how a database is constructed
Physical schema
Logical Schema
Schema
A physical data model (or database design) is a representation of a data design which takes into
account the facilities and constraints of a given database management system.
A physical schema is hidden beneath the logical schema, and can usually be changed easily
without affecting application programs
A logical schema is a data model of a specific problem domain expressed in terms of a particular data management technology.
DATA MODELS
Underlying the structure of a databse is the data model: a collection of conceptual tools for describing data, data relationships , data semantics and consistency constraints.
Data Models
Relational
Entity-Relationship
Object-Based
Semistructured
The purpose of the relational model is to provide a declarative method for specifying data
and queries: users directly state what information the database contains and what
information they want from it, and let the database management system software take care of describing data structures for storing the data
and retrieval procedures for answering queries.
An entity–relationship model (ER model) is a data model for describing the data or information aspects of a business domain or its process requirements, in an abstract way that lends itself to ultimately being
implemented in a database such as a relational database. The main components of ER models
are entities (things) and the relationships that can exist among them.
Entity–relationship modeling was developed by Peter Chen
Object-oriented database management sytems allow object-oriented programmers to develop the product, store them as objects, and replicate or modify existing
objects to make new objects within the OODBMS. Because the database is integrated with the programming
language, the programmer can maintain consistency within one environment, in that both the OODBMS and
the programming language will use the same model of representation. Relational DBMS projects, by way of
contrast, maintain a clearer division between the database model and the application.
The semi-structured model is a database model where there is no separation between the data and the schema,
and the amount of structure used depends on the purpose.
This is in contrast to the data models mentioned earlier where every data item of a particular type must have the
same set of attributes.
Eg: XML
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