The document discusses the objectives and components of the ANSI-SPARC three-level database architecture. The architecture includes an external, conceptual, and internal level. The external level defines users' views, the conceptual level defines entity relationships and constraints, and the internal level defines physical storage. Mappings allow translation between levels. The architecture aims to provide logical and physical data independence so changes to one level do not affect others.
Normalization is the process of removing redundant data from your tables to improve storage efficiency, data integrity, and scalability.
Normalization generally involves splitting existing tables into multiple ones, which must be re-joined or linked each time a query is issued.
Why normalization?
The relation derived from the user view or data store will most likely be unnormalized.
The problem usually happens when an existing system uses unstructured file, e.g. in MS Excel.
Normalization is the process of removing redundant data from your tables to improve storage efficiency, data integrity, and scalability.
Normalization generally involves splitting existing tables into multiple ones, which must be re-joined or linked each time a query is issued.
Why normalization?
The relation derived from the user view or data store will most likely be unnormalized.
The problem usually happens when an existing system uses unstructured file, e.g. in MS Excel.
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
Part One of Entrepreneurship Lecture Notes on Students Enterprise Club at www.studentsenterpriseclub.com.
This is a Study guide for intending Entrepreneurs.
CS3270 - DATABASE SYSTEM - Lecture (2)Dilawar Khan
Topics Covered:
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The Three-Level ANSI-SPARC Architecture
Database Languages
Data Models and Conceptual Modeling
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3. Objectives of Three-Level
Architecture
ANSI-SPARC Three Level Architecture
All users should be able to access same data
but have a different customized view
A user’s view is immune to changes made in
other views
Users should not need to know physical
database storage details
4. Objectives of Three-Level
Architecture..
DBA should be able to change database
storage structures without affecting the
users’ views
Internal structure of database should be
unaffected by changes to physical aspects of
storage
DBA should be able to change conceptual
structure of database without affecting all
users
6. ANSI-SPARC Three-Level
Architecture..
External Level
Users’ view of the database
Describes that part of database that is relevant to a
particular user
Different views may have different representation of same
data (e.g. different date formats, age derived from DOB
etc.)
7. ANSI-SPARC Three-Level
Architecture..
Conceptual Level
Community view of the database
Describes what data is stored in database and
relationships among the data
Along with any constraints on data
Independent of any storage considerations
i. all entities, their attributes, and their relationships;
ii. the constraints on the data;
iii. semantic information about the data
security and integrity information.
8. ANSI-SPARC Three-Level
Architecture..
Internal Level
storage space allocation for data and indexes;
record descriptions for storage (with stored
sizes for data items); n
record placement; n
data compression and data encryption
techniques.
9. ANSI-SPARC Three-Level
Architecture..
Internal Level
Physical representation of the database on the computer
Describes how the data is stored in the database
physical implementation of the database to achieve
optimal runtime performance and storage space
utilization
Data structures and file organizations used to store data
on storage devices
Interfaces with the operating system access methods to
place the data on the storage devices, build the indexes,
retrieve the data, and so on
11. Schemas
External Schemas
Also called subschemas
Multiple schemas per database
Corresponds to different views of data
Conceptual Schema
Describes all the entities, attributes, and relationships
together with integrity constraints
Only one schema per database
12. Schemas..
Internal Schema
A complete description of the internal model, containing
the definitions of stored records, the methods of
representation, the data fields, and the indexes and
storage structures used
Only one schema per database
13. Mappings
The DBMS is responsible for mapping
between these three types of schema:
The DBMS must check that each external schema is
derivable from the conceptual schema, and it must use the
information in the conceptual schema to map between
each external schema and the internal schema
Types of mappings
Conceptual/Internal mapping
External/Conceptual mapping
14. Conceptual/Internal Mapping
Enables the DBMS to
Find the actual record or combination of records in
physical storage that constitute a logical record in the
conceptual schema,
Together with any constraints to be enforced on the
operations for that logical record
It also allows any differences in entity names, attribute
names, attribute order, data types, and so on, to be
resolved
16. Instances
Database Schema
Description of database (also called intension)
Specified during design phase
Remain almost static
Database Instance
Data in the database at any particular point in time
Dynamic (changes with the time)
Also called an extension (or state) of database
17. Data Independence
Logical Data Independence
Refers to protection of external schemas to changes in
conceptual schema
Conceptual schema changes (e.g. addition/removal of
entities)
Should not require changes to external schema or rewrites
of application programs
18. Data Independence
Physical Data Independence
Refers to immunity of conceptual schema to changes in
the internal schema
Internal schema changes (e.g. using different file
organizations, storage structures, storage devices etc.)
Should not require change to conceptual or external
schemas
The way users perceive the data is called the external level. The way the DBMS and the operating system perceive the data
is the internal level, where the data is actually stored using the data structures and file organizations.
in the DreamHome case study, we may wish to view the age of a member of staff. However, it is unlikely that ages would be stored, as this data would have to be updated daily. Instead, the member of staff’s date of birth would be stored and age would be calculated by the DBMS when it is referenced. Views may even include data combined or derived from several entities.
