Lecture 1 of Advanced Databases

Basic Concepts

Instructor: Mr.Ahmed Al Astal

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Basic Concepts

Introduction and basic definitions

ER Modeling.

ER-Relational Schema Mapping

Database Languages.

FDs and Normalization .

Agenda

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Basic Concepts

Database : A set of related data.

Database management Systems (DBMS): software package/ system to facilitate the creation and maintenance of a computerized database.

Database System: The DBMS software together with the data itself. Sometimes, the applications are also included.

Introduction and basic definitions

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Basic Concepts

Database Administrator (DBA).

Database Designer.

End Users

Application Programmers.

Database Users

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Basic Concepts

ER Model: is a logical model that used for describing Entities and the relationships between these entities.

ER Symbols:

ER Modeling

Meaning

ENTITY TYPE

WEAK ENTITY TYPE

RELATIONSHIP TYPE

IDENTIFYING RELATIONSHIP TYPE

ATTRIBUTE

Symbol Meaning

KEY ATTRIBUTE

MULTIVALUED ATTRIBUTE

COMPOSITE ATTRIBUTE

DERIVED ATTRIBUTE

Symbol

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Basic Concepts

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Basic Concepts

Mapping of Regular Entity Types

Mapping of Weak Entity Types

Mapping of Binary 1:1 Relation Types

Mapping of Binary 1:N Relationship Types.

Mapping of Binary M:N Relationship Types.

Mapping of Multi-valued attributes.

Mapping of N-ary Relationship Types

ER to Relational Mapping

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Basic Concepts

Procedural Languages: Relational Algebra, Relational Calculus, Cobol,….

Non Procedural Languages: SQL

DDL: Create, Alter Table, Drop Table

DML: Select, Update, Delete

Database Languages

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Basic Concepts

Functional dependencies (FDs) are used to specify formal measures of the "goodness" of relational designs.

FDs are constraints that are derived from the meaning and interrelationships of the data attributes.

SSN ENAME

Level, Experience_Years Salary

FDs & Normalization

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Basic Concepts

IR1. (Reflexive)

• If Y ⊇X, then X -> Y

IR2. (Augmentation)

• If X Y, then XZ YZ

(Notation: XZ stands for X U Z)

IR3. (Transitive)

• If X Y and Y Z, then X -> Z

Inference Rules for FDs

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Basic Concepts

Some additional inference rules that are useful:

(Decomposition)

• If X YZ, then X Y and X Z

(Union)

• If X Y and X Z, then X YZ

(Pseudo transitivity)

• If X Y and WY Z, then WX Z

Inference Rules for FDs

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Basic Concepts

Normalization: The process of decomposing unsatisfactory "bad" relations by breaking up their attributes into smaller relations

First Normal Form.

Second Normal Form.

Third Normal Form.

BCNF

Normalization

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Basic Concepts

Disallows

- composite attributes

- Multi-valued attributes

- nested relations; attributes whose values for an individual tuple are non-atomic

First Normal Form

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Basic Concepts

Given a relation R and a set of FDs F hold on R,

R is in BCNF (i.e. R is a good relation) iff for each FD in the form α -> β in F : α must be a super key

• If any FD fails then we divide the relation into tow relation R1(α , β) , R2(R- β).

BCNF (Boyce-Coded Normal Form)

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Basic Concepts

Given a relation R and a set of FDs F hold on R, R is in 3NF iff for each FD in the form α β in F at least one of the following conditions satisfies:

- α must be a key for R OR

- Each attribute in β is Prime attribute

If any FD fails then we divide the relation into tow relations:

R1(α , Non Prime Attributes in β ) ,

R2(R- Non Prime Attributes in β ).

Third Normal Form 3NF

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Basic Concepts

Given a relation R and a set of FDs F hold on R, R is in 3NF iff for each FD in the form α β in F at least one of the following conditions satisfies:

- α must be a key for R OR

- Each attribute in β is Prime attribute

- α is not a subset of any key

If any FD fails then we divide the relation into tow relations:

R1(α , Non Prime Attributes in β ) ,

R2(R- Non Prime Attributes in β ).

Third Normal Form 2NF