4. DATA
VS
DATABASE
1. Storage
Besides computers,
databases can even be
maintained in physical
ledgers, books or papers.
In a database
management
system (DBMS), all
the records are
maintained only on
a computer.
2.
Data
Retrieval
The retrieval of
information from the
databases can be done
manually, through
queries or by using
programs (C, C++, Java
etc.).
We can retrieve the
data from the
database
management
system through
queries written in
SQL.
3. Speed
As databases can be
handled manually or via
computers, when SQL is
not used to retrieve
information, it can be
very slow.
As a computer
system is involved
in a database
management
system, the
retrieval of
information is very
quick.
5. DATA
VS
DATABASE
4. Access
The databases are not
designed for a large
number of people who can
access data at the same
time, rather it is designed
for a very small number of
people (preferably few
people) who access data at
different times.
The database
management
system is designed
for a large number
of people who can
access the data at
the same time.
5.
Data
Manipulation
In case of the databases,
very less information can
be modified at a time.
In the database
management
system (DBMS), a
lot of information
can be changed at
one time (as it can
have many users
using it at the same
time).
6.
Backup and
Recovery
The databases do not
ensure that the data will
be available after failure
arises.
The database
management
system (DBMS)
ensures that the
data will always be
6. Database
Management
System(DBMS)
Collection of interrelated data
Set of programs to access the data
DBMS contains information about a particular
enterprise
DBMS provides an environment that it both
convenient and efficient to use
7. Purposeof
Database
Systems
Database management systems were developed to handle
the following difficulties of typical file-processing systems
supported by conventional operating systems.
Data redundancy and inconsistency
Difficulty in accessing data
Data isolation – multiple files and formats
Integrity problems
Atomicity of updates
Concurrent access by multiple users
Security problems
8. Characteristics
ofDBMS
Real-world entity
Relation-based tables
Isolation of data and application
Less redundancy
Consistency
Query Language
ACID Properties (Atomicity, Consistency, Isolation,
and Durability )
Multiuser and Concurrent Access
Multiple views
Security
10. PhysicalData
Level
The physical schema describes details of how data is
stored: files, indices, etc. on the random access disk
system. It also typically describes the record layout of
files and type of files (hash, b-tree, flat).
11. ConceptualData
Level
Also referred to as the Logical level
Hides details of the physical level.
In the relational model, the conceptual schema
presents data as a set of tables.
The DBMS maps data access between the
conceptual to physical schemas automatically.
Physical schema can be changed without
changing application:
DBMS must change mapping from conceptual to
physical.
Referred to as physical data independence.
12. ExternalData
Level
In the relational model, the external schema also
presents data as a set of relations. An external schema
specifies a view of the data in terms of the conceptual
level. It is tailored to the needs of a particular category
of users. Portions of stored data should not be seen by
some users and begins to implement a level of security
and simplifies the view for these users
Examples:
Students should not see faculty salaries.
Faculty should not see billing or payment data.
14. DATAMODELS
A conceptual data model identifies the highest-level
relationships between the different entities. Features
of conceptual data model include:
Includes the important entities and the relationships
among them.
No attribute is specified.
No primary key is specified.
Conceptual Data Model
16. LogicalData
Model
A logical data model describes the data in as much detail as
possible, without regard to how they will be physical implemented
in the database. Features of a logical data model include:
Includes all entities and relationships among them.
All attributes for each entity are specified.
The primary key for each entity is specified.
Foreign keys (keys identifying the relationship between different
entities) are specified.
Normalization occurs at this level.
The steps for designing the logical data model are as follows:
Specify primary keys for all entities.
Find the relationships between different entities.
Find all attributes for each entity.
Resolve many-to-many relationships.
Normalization.
18. PhysicalData
Model
Physical data model represents how the model will be built in the database. A
physical database model shows all table structures, including column name,
column data type, column constraints, primary key, foreign key, and
relationships between tables. Features of a physical data model include:
Specification all tables and columns.
Foreign keys are used to identify relationships between tables.
Denormalization may occur based on user requirements.
Physical considerations may cause the physical data model to be quite
different from the logical data model.
Physical data model will be different for different RDBMS. For example,
data type for a column may be different between MySQL and SQL Server.
The steps for physical data model design are as follows:
Convert entities into tables.
Convert relationships into foreign keys.
Convert attributes into columns.
Modify the physical data model based on physical constraints / requirements
20. Database
Schema
A database schema is the skeleton structure that
represents the logical view of the entire database. It
defines how the data is organized and how the
relations among them are associated. It formulates all
the constraints that are to be applied on the data.
A database schema defines its entities and the
relationship among them. It contains a descriptive
detail of the database, which can be depicted by means
of schema diagrams. It’s the database designers who
design the schema to help programmers understand
the database and make it useful.
22. DatabaseSchema
Physical Database Schema − This schema pertains to the actual
storage of data and its form of storage like files, indices, etc. It
defines how the data will be stored in a secondary storage.
Logical Database Schema − This schema defines all the logical
constraints that need to be applied on the data stored. It defines
tables, views, and integrity constraints.