chap02database design methodology-12-10-2011

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Phase 02

Conceptual Database Design:

It consists of two phases —

a)Conceptual schema designb)Transaction and application design



a)Conceptual schema design

Goal is to design conceptual schemadesign of databasestructure,meaning,relationships etc.

Is a stable description of databasecontents

Imp for database users and applicationdesigners.

Diagrammatic description is vehicle of communication.



Approaches to conceptual schemadesign

A)Centralized schema design approach.

B)View integration approach.



Strategies for conceptual schemadesign

Top-down strategy

Bottom-up strategy

Inside-out strategy Mixed strategy



Schema (view) Integration

First design individual schema and thenmerge them.

Design of the schema simplified.

So methodology for integrating views intoglobal schema required.



Schema integration divided intosubtasks:

1.Indentifying corrospondence and conflictsamong the schemas->

-Represents same real world objects.

-And this corrospondance identified fromdifferent views before integration.



During this process several types of conflicts among the schema should be

identified:i) Naming conflicts:

Two types:->

a) synonyms:two schema using the two differentname for describing the same concept.

e.g. customer in one schema may havesame meaning as that of other schema

client.



b) Homonym :

when same name used to describe thedifferent concepts.

e.g. entity type part in one describes

computer parts in one schema andfurniture parts in other schema.



ii) Type conflicts:

-same concept used in two schema by

different modeling constructs.-like department used as entity in one

schema and as an attribute in other

schemas.

iii) Domain conflicts:

An attribute have two different domains intwo schemas.



e.g. dept_id used as integer in one andchar in other.

iv) Conflicts among constraints:

-Two schema have different constraints.

-different structural constraints onrelationship

e.g. works_on relationship may have 1:N inone schema

And M:N in other schema.



2) Modifying views to confirm to oneanother.

->Schema modified according to anotherschemas that are related to each other.

->conflicts are resolved.

3) Merging of views:

->global schema is created by mergingindividual schemas.

->Most difficult step.



4) Restructing:

Global schema is analyzed and restructuredComplexity is removed.



Strategies for view integration process

Binary ladder integration:->Two similar schemas are integrated firstand then resulting schema integrated with

another schema.->process continues till all schemas are

integrated.



N-ary integration:

->all schemas are integrated into oneprocedure.

->requires computerized tools for design.

->yet not available in market.

Binary balanced strategy:

->pairs of schemas are integrated first.

->repeat till final global schema is created.



Mixed Strategy:

Schemas are partitioned into groups basedon their similarity.

And each group is integrated separately.



Phase 2b:Transaction Design Identify transactions on the database.

Functional characteristics of transactions.in early stages. Knowing Importance of transactions at design time.

Common technique is identify Input,output, and

functional behavior. Transactions are of three types:

a) Retrieval transactions:

Display datab) Update transactions:Modify data.c)Mixed transactions:Display data and moidify data.



Phase 3:Choice of DBMS

Technical ,economical and politics of organization.

Nontechnical includes financial status.

Economical and organizational factorsthat affect the choice of DBMS:

1) Software acquisition cost:

2) Maintenance Cost:Keep Version uptodate

3) Hardware acquisition cost:



4)Database creation and conversion cost:

5) Personal Cost:Reorganization of dataprocessing department.

6)Training cost:

7)Operating Cost:



Moving from file based to datacentered approach:

Depends on following factors:

1)Data complexity:

Need for DBMS that handles data

2)Sharing among application: greatersharing greater redundancy among files soneed DBMS.



3)Dynamically evolving or growing data:

Data changes frequently.

4) Frequency of ad hoc requests of data:

5)Data volume and need of control:



Several Economic and organizationalfactors

1)Organization wide adoption of certainphilosophy:

Dominant factor that affect acceptabilityof data model, development methodologyand design tools.

2)Familiarity of personal with the system:

Reduces training cost and learning time.



3)Availability of vendor services:

-For solving problems is very important.-Moving from non-DBMS to DBMS.



Hardware

Versions that run on manyhardware/software configurations.

Need for backup, recovery, integrity, security



Phase 4:Data Model Mapping

It's LOGICAL DATABASE DESIGN

1)System independent mapping:

Independent of DBMS.

Features not considered.

2)Tailoring the schema to a specific DBMS:

While designing the database features of DBMS considered.



Phase 5:Physical Database design

Chose storage structures Chose access path.

indexing, linking related records.Criteria for choosing physical database

design:

A) Response Time

submit database transaction and

receiving response.



B) Space utilization:

Storage space used by database files.

C)Transaction throughput:

Average number of transactions processedper minute.



Phase 6:Database systemImplementation and Tuning

After logical and physical designcomplemented, implement databasesystem.



Advanced SQL

Data types in SQL



What is SQL? - Stands forStructured Query Language

What is SQL? SQL stands for Structured Query Language and is the lingua franca in the

database world. SQL is a standard that is used by all database vendors andprogrammers to define, extract and access the information that is stored indatabases. SQL began life as an IBM creation but was standardized by the American National Standards Institute (ANSI) and the InternationalOrganization for Standardization (ISO) as ANSI/ISO SQL in 1988. Since then ANSI/ISO SQL standard continued to evolve. The ANSI-SQL group has sincepublished three standards over the years:

1. SQL89 (SQL1) 2. SQL92 (SQL2) 3. SQL99 (SQL3) SQL is a query language. It is English-like and easy to use. However,

although there are more than 90 SQL reserved words, most programmersseldom use more than the following handful of commands - SELECT,INSERT, UPDATE, DELETE, FROM, WHERE, HAVING, BETWEEN, LIKE, OR, AND, NOT, IN, ORDER, GROUP and BY.



The most central data modelling notions included inSQL3 are illustrated in and support specification of:

Classification hierarchies,

Embedded structures that support composite attributes,

Collection data-types (sets, lists/arrays, and multi-sets)that can be used for multi-valued attribute types,

Large OBject types, LOBs, within the DB, as opposed torequiring external storage, and

User defined data-types and functions (UDT/UDF) thatcan be used to define complex structures and derivedattribute value calculations, among many other functionextensions.

chap02database design methodology-12-10-2011

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