1. DCT 2053 DATABASE CONCEPT Chapter 2.2 CONTINUE
The Relational Database Model

2. A Logical View of Data
Relational database model’s structural and data independence enables us to view data logically rather than physically.
The logical view allows a simpler file concept of data storage.
The use of logically independent tables is easier to understand.
Logical simplicity yields simpler and more effective database design methodologies.
Nur Sukinah Aziz
TATiUC

3. A Logical View of Data
Relational database model’s structural and data independence enables us to view data logically rather than physically.
The logical view allows a simpler file concept of data storage.
The use of logically independent tables is easier to understand.
Logical simplicity yields simpler and more effective database design methodologies.
Nur Sukinah Aziz
TATiUC

4. A Logical View of Data Entities and Attributes
An entity is a person, place, event, or thing for which we intend to collect data.
University -- Students, Faculty Members, Courses
Airlines -- Pilots, Aircraft, Routes, Suppliers
Each entity has certain characteristics known as attributes.
Student -- Student Number, Name, GPA, Date of Enrollment, Data of Birth, Home Address, Phone Number, Major
Aircraft -- Aircraft Number, Date of Last Maintenance, Total Hours Flown, Hours Flown since Last Maintenance
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TATiUC

5. A Logical View of Data Entities and Attributes
A grouping of related entities becomes an entity set.
The STUDENT entity set contains all student entities.
The FACULTY entity set contains all faculty entities.
The AIRCRAFT entity set contains all aircraft entities.
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TATiUC

6. A Logical View of Data Tables and Their Characteristics
A table contains a group of related entities -- i.e. an entity set.
The terms entity set and table are often used interchangeably.
A table is also called a relation.
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7. Summary of the Characteristics
of a Relational Table
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8. STUDENT Table Attribute Values
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9. KEY Consists of one or more attributes that determine other attributes
Primary key (PK) is an attribute (or a combination of attributes) that uniquely identifies any given entity (row)
The primary key of one table appears again as the link (foreign key) in another table.
If the foreign key contains either matching values or nulls, the table(s) that make use of such a foreign key are said to exhibit referential integrity.
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12. KEY A key helps define entity relationships.
The key’s role is based on a concept known as determination, which is used in the definition of functional dependence.
The attribute B is functionally dependent on A if A determines B.
An attribute that is part of a key is known as a key attribute.
A multi-attribute key is known as a composite key.
If the attribute (B) is functionally dependent on a composite key (A) but not on any subset of that composite key, the attribute (B) is fully functionally dependent on (A).
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13. Relational Database Keys
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14. Integrity Rules Revisited
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15. NULL Values No data entry Not permitted in primary key
Should be avoided in other attributes
Can represent
An unknown attribute value
A known, but missing, attribute value
A “not applicable” condition
Can create problems in logic and using formulas
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16. Controlled Redundancy
Makes the relational database work
Tables within the database share common attributes that enable us to link tables together
Multiple occurrences of values in a table are not redundant when they are required to make the relationship work
Redundancy is unnecessary duplication of data
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17. Relational Database Operators
Relational algebra
Defines theoretical way of manipulating table contents using relational operators:
SELECT
PROJECT
JOIN
INTERSECT
Use of relational algebra operators on existing tables (relations) produces new relations
UNION
DIFFERENCE
PRODUCT
DIVIDE
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18. Relational Database Operators(cont’d)
Union:
Combines all rows from two tables, excluding duplicate rows
Tables must have the same attribute characteristics
Intersect:
Yields only the rows that appear in both tables
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19. Union
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20. Intersect
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21. Relational Database Operators(cont’d)
Difference
Yields all rows in one table not found in the other table—that is, it subtracts one table from the other
Product
Yields all possible pairs of rows from two tables
Also known as the Cartesian product
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22. Difference
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23. Difference
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24. Relational Database Operators(cont’d)
Select
Yields values for all rows found in a table
Can be used to list either all row values or it can yield only those row values that match a specified criterion
Yields a horizontal subset of a table
Project
Yields all values for selected attributes
Yields a vertical subset of a table
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25. Select
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26. Project
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27. Relational Database Operators(cont’d)
Join
Allows us to combine information from two or more tables
Real power behind the relational database, allowing the use of independent tables linked by common attributes
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29. Natural Join
Links tables by selecting only rows with common values in their common attribute(s)
Result of a three-stage process:
PRODUCT of the tables is created
SELECT is performed on Step 1 output to yield only the rows for which the AGENT_CODE values are equal
Common column(s) are called join column(s)
PROJECT is performed on Step 2 results to yield a single copy of each attribute, thereby eliminating duplicate columns
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32. Natural Join (cont’d) Final outcome yields table that
Does not include unmatched pairs
Provides only copies of matches
If no match is made between the table rows,
the new table does not include the unmatched row
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33. Other Forms of Join Equijoin
Links tables on the basis of an equality condition that compares specified columns of each table
Outcome does not eliminate duplicate columns
Condition or criterion to join tables must be explicitly defined
Takes its name from the equality comparison operator (=) used in the condition
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34. Other Forms of Join Theta join
is an equiJOIN that compares specified columns of each table using a comparison operator other than the equality comparison operator.
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35. Outer Join
Matched pairs are retained and any unmatched values in other table are left null
In outer join for tables CUSTOMER and AGENT, two scenarios are possible:
Left outer join
Yields all rows in CUSTOMER table, including those that do not have a matching value in the AGENT table
Right outer join
Yields all rows in AGENT table, including those that do not have matching values in the CUSTOMER table
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38. Divide
DIVIDE requires the use of one single-column table and one two-column table
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39. The Data Dictionary and the System Catalog
Used to provide detailed accounting of all tables found within the user/designer-created database
Contains (at least) all the attribute names and characteristics for each table in the system
Contains metadata—data about data
Sometimes described as “the database designer’s database” because it records the design decisions about tables and their structures
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41. The Data Dictionary and the System Catalog
System catalog is a very detailed system data dictionary that describes all objects within the database.
System catalog is a system-created database whose tables store the database characteristics and contents.
System catalog tables can be queried just like any other tables.
System catalog automatically produces database documentation.
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42. Relationships within the Relational Database
E-R Diagram (ERD)
Rectangles are used to represent entities.
Entity names are nouns and capitalized.
Diamonds are used to represent the relationship(s) between the entities.
The number 1 is used to represent the “1” side of the relationship.
The letter M is used to represent the “many” sides of the relationship.
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43. Relationships within the Relational Database(cont’d)
Three Types of Relationships:
One-to-many relationships (1:M)
Relational modeling ideal
Should be the norm in any relational database design
A painter paints many different paintings, but each one of them is painted by only that painter.
PAINTER (1) paints PAINTING (M)
Many-to-many relationships (M:N)
Must be avoided because they lead to data redundancies
An employee might learn many job skills, and each job skill might be learned by many employees.
EMPLOYEE (M) learns SKILL (N)
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44. Relationships within the Relational Database(cont’d)
One-to-one relationships (1:1)
Should be rare in any relational database design
Each store is managed by a single employee and each store manager (employee) only manages a single store.
EMPLOYEE (1) manages STORE (1)
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45. The 1:1 Relationship Relational database norm
Found in any database environment
One entity can be related to only one other entity, and vice versa
Often means that entity components were not defined properly
Could indicate that two entities actually belong in the same table
Sometimes 1:1 relationships are appropriate
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46. The 1:1 Relationship Between PROFESSOR and DEPARTMENT
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53. The M:N Relationship
Can be implemented by breaking it up to produce a set of 1:M relationships
Can avoid problems inherent to M:N relationship by creating a composite entity or bridge entity
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56. Linking Table Implementation of a composite entity
Yields required M:N to 1:M conversion
Composite entity table must contain at least the primary keys of original tables
Linking table contains multiple occurrences of the foreign key values
Additional attributes may be assigned as needed
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61. Data Redundancy Revisited
Data redundancy leads to data anomalies
Such anomalies can destroy database effectiveness
Foreign keys
Control data redundancies by using common attributes shared by tables
Crucial to exercising data redundancy control
Sometimes, data redundancy is necessary
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