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Transcript of GAMA ILP Course Ware SDLC Data Base Design New
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Data Base Design
UST Global
120 Vantis AlisoViejo CA 92656Phone: (949) 716-8757www.ust-global.com
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Concepts of Database Designing
Database Designing is the process of convertingSystem Requirements to a database model.
A typical database design lifecycle constitutes thefollowing
1. Conceptual Modeling Data Flow Diagrams
2. Logical Modeling ER Diagrams
Data Dictionary
Normalization First NF
Second NF
Third NF
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Concepts of Database Designing Contd..
3.Physical Database Design Storage Designing
Logical Storage
Physical Storage
Data Flow Design
Data Integrity Referential Integrity
Rules and Constraints
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To document the business informationrequirements
To identify reuse requirements andopportunities
To document data requirements basedfunctional activity and/or business rules
To assist in identification of redundantprocesses
To guide and support consistent dataadministration
Purpose of Database Modeling
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Logical Designing
Any system has or should satisfy a fewimportant characteristics. They are: A well defined system boundary
A well defined set of inputs and outputs
A data store that stores information
Logical Designing is the process of creatingthe logical architecture of a system. Thelogical architecture comprises of defining thelogical components that influence the
system like processes, data flow, entities etc.
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Logical Designing Contd..
Following are the various approaches thatare being used as part of the designingprocess. Data Flow Diagrams
Entity Relationship Diagrams
Data Dictionary
Decision Tables and Decision Trees
State Transition Diagrams
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Entity Relationship Diagrams (ERD)
While Data Flow Diagrams show the
flow of data between processes, Entity
Relationship diagrams show the
relationship between data. An ER diagram is an effective tool to
demonstrate and document the data
relationships which helps bettermanagement and maintenance of data.
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ERD
Attribute An Attribute is a property that explainsan entity.
Relationship A Relationship is a definition on theassociation or interaction between Entities
We can classify Relationships according to twocharacteristics
Optionality
Mandatory Relationship
Optional Relationship
Cardinality One-to-One
One-to-Many
Many-to-Many
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ERD - Notation
Data Element
Relationship
Associated Object
Cardinality Exactly one
Cardinality Zero or one
Cardinality Mandatory Many
Cardinality Optional Many
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Developing an ERD
Developing an ERD requires an
understanding of the system and its
components.
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How do we start an ERD?
1. Define Entities: these are usually nouns
used in descriptions of the system, in the
discussion of business rules, or in
documentation; identified in the narrative2. Define Relationships: these are usually
verbs used in descriptions of the system or
in discussion of the business rules (entity
______ entity); identified in the narrative
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How do we start an ERD? Contd..
3. Add attributes to the relations; these are
determined by the queries, and may also
suggest new entities, e.g. grade; or they
may suggest the need for keys or identifiers4. Add cardinality to the relations; Many-to-
Many must be resolved to two One-to-Many
using an additional entity. Usually
automatically happens. Sometimes involvesintroduction of a link entity (which will be all
foreign key) Examples: Patient-Drug
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How do we start an ERD? Contd..
5. This flexibility allows us to consider a variety
of questions such as:
Which beds are free?
Which assistants work forDr. X?
What is the least expensive prescription?
How many doctors are there in the
hospital? Which patients are family related?
6. Represent that information with symbols
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ER Diagram Examples
In a company, each division is managed by only one manager and eachmanager manages only one division
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In a college, every student takes as many courses and every course is taken bymany students
Among the mobile manufacturing companies, a company manufactures manycars, but a given car is manufactured in only one company
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Data Dictionary
A Data Dictionary is an organized documentation ofData Elements, Data Structures and Data Flows.
Data Element - Piece of data, which cannot bedecomposed further in the current context of the
system. Examples are purchase_order_no,employee_name, interest_rate, etc.
Data Structure - Composed of data elements or otherdata structures. Examples are Customer_details,which may be composed ofCustomer_name and
Customer_address. Data Flow is composed of data structures and/or
data elements. Definitions of dependent datastructures/data elements precede the definition ofdata flow. While defining the data flow the
connecting points should be mentioned.16
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Transition from Logical to Physical
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Logical Physical
Data Entities Tables
Attributes Columns/Fields
Entity Instances Rows/Records
Relationships/Cardinality Primary/Foreign Keys
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Database Normalization
Database Normalization is the process of efficiently organizing data to achievethe following goals
Avoid data redundancy
Ensure data integrity.
There are multiple levels of normalization. A typical application databaseshould be ideally at the 3rd normal form
First Normal Form
A relation R is in first normal form (1NF) if and only if all underlyingdomains contain atomic values only.
Remove redundant columns
Primary Key
Second Normal Form
A relation R is in second normal form (2NF) if and only if it is in 1NF and
every nonkey attribute is fully dependent on the primary key. Enforce primary key-foreign key relationship
Third Normal Form
A relation R is in third normal form (3NF) if and only if it is in 2NF and everynonkey attribute is nontransitively dependent on the primary key.
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First Normal Form (1NF)
There are no repeating or duplicate
fields.
Each cell contains only a single value.
Each record is unique.
Identified by primary key
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Example
Table is not in first normal form
because:
Multiple items in color field
Duplicate records / no primary key
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Item Colors Price Tax
T-shirt Red, blue 12.00 0.60
Polo Red, yellow 12.00 0.60
T-shirt Red, blue 12.00 0.60
Sweatshirt Blue, black 25.00 1.25
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Example
Item Color Price Tax
T-shirt Red 12.00 0.60
T-shirt Blue 12.00 0.60
Polo Red 12.00 0.60
Polo Yellow 12.00 0.60Sweatshirt Blue 25.00 1.25
Sweatshirt Black 25.00 1.25
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Table is now in first normal form
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Second Normal Form (2NF)
All non-key fields depend on all
components of the primary key.
Guaranteed when primary key is a single
field.
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Example
Item Color Price Tax
T-shirt Red 12.00 0.60
T-shirt Blue 12.00 0.60
Polo Red 12.00 0.60
Polo Yellow 12.00 0.60Sweatshirt Blue 25.00 1.25
Sweatshirt Black 25.00 1.25
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Table is not in second normal formbecause
Price and Tax depend on item, but not
color
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Example
Item Color
T-shirt Red
T-shirt Blue
Polo Red
Polo YellowSweatshirt Blue
Sweatshirt Black
Item Price Tax
T-shirt 12.00 0.60
Polo 12.00 0.60
Sweatshirt 25.00 1.25
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Tables are now in second normal form
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Third Normal Form (3NF)
No non-key field depends upon
another.
All non-key fields depend only on the
primary key.
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Example
Item Color
T-shirt Red
T-shirt Blue
Polo Red
Polo YellowSweatshirt Blue
Sweatshirt Black
Item Price Tax
T-shirt 12.00 0.60
Polo 12.00 0.60
Sweatshirt 25.00 1.25
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Tables are not in third normal formbecause
Tax depends on price, not item
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Example
Item Color
T-shirt Red
T-shirt Blue
Polo Red
Polo Yellow
Sweatshirt Blue
Sweatshirt Black
Item Price
T-shirt 12.00
Polo 12.00
Sweatshirt 25.00
Price Tax
12.00 0.60
25.00 1.25
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Tables are now in third normal form
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Relationships
Relationships are created between tablesusing the primary key field and a foreign keyfield
One to One Relationship - One record in atable relates to one record in another table
One to Many Relationship - One record in atable can relate to many records in anothertable
Many to Many Relationship - Many records inone table can relate to many records inanother table
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Relationships in the Example
Item Color
T-shirt Red
T-shirt Blue
Polo Red
Polo Yellow
Sweatshirt Blue
Sweatshirt Black
Item Price
T-shirt 12.00
Polo 12.00
Sweatshirt 25.00
Price Tax
12.00 0.60
25.00 1.25
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One-to-one
One-to-many
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Database Integrity
Primary Key
Clustered
Non-Clustered
Foreign key
Rules and Constraints
Check
Defaults
Triggers
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Thank you!!