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Ism normalization pine valley 2012

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Ism normalization pine valley 2012 Presentation Transcript

  • 1. NORMALIZATION
    Prof. Sridhar Vaithianathan
  • 2. Entities, Attributes and Relationship
    Strong Entity Vs Weak entity ( EMPLOYEE & DEPENDENT)
    Simple Vs Composite Attributes
    Single Valued Vs Multi Valued Attributes
    Stored Vs Derived Attributes
    Identifier Attribute – Primary Key
    Composite Identifier
    Foreign Key
    Sub-Type Vs Super Type Relationship
  • 3. Properties of Relations
    Each relation (or table) in a database has a unique name.
    An entry at the intersection of each row and column is atomic (single valued).there can be no multivalued attributes in a relation.
    Each row (record) is unique; no two rows in a relation are identical.
    Each attribute(or column) within a table has a unique name.
    The sequence of columns/rows (left to right/top to bottom) is insignificant.
  • 4.
  • 5. Integrity Constraints
    Domain Constraints: All of the values that appear in a column of a relation must be taken from the same domain.
    A domain is the set of values that may be assigned to an attribute. [Domain definition usually consists of: domain name, meaning, data type, size (length), and allowable values/range.]
    Entity Integrity Constraint: No primary key attribute (or component of primary key attribute) may be null.
    Null: A value that may be assigned to an attribute when no other value applies or when the applicable value is unknown.
    Null is neither numeric zero nor string of blanks.
    In reality null is not a value but rather absence of a value
    Referential Integrity Constraint: Either each foreign key value must match a primary key value in another relation or the foreign key value must be null. ( Eg : Student who has not been assigned any faculty as mentor)
  • 6. Logical Database Design
    Top-down approach > E-R modeling
    Bottom-up approach > Normalization.
    Databases : Relational Vs Non-Relational.
    What is Normalization?
    It is a formal process for deciding which attributes should be grouped together in relation
    It is a step by step decomposition of complex records into simple records and thereby reducing redundancy
    Why Normalize ?
    Normalization reduces redundancy. Redundancy is the unnecessary repetition of data
  • 7. Redundancy can lead to:
    Inconsistencies– Errors are more likely to occur when facts are repeated
    Update Anomalies
    - Inserting, modifying and deleting data may cause inconsistencies
    - High likelihood of updating or deleting data in one table while omitting to make corresponding changes in other relations
    A fully normalized record consists of:
    A primary key that identifies an entity
    A set of attributes that describe the entity
    Normal forms (NF) are table structures with minimum redundancy
  • 8. Functional Dependency
    Normalization theory is based on the fundamental notion of functional dependency.
    Given a relation R, attribute B is functionally dependent on A if , for every valid instance of A, that value of A uniquely determines the value of B.
    The functional dependency of B on A is represented as below
    A B
    Example: Suppose entity CUSTOMER has the following attributes
    Cust_Code, Name, Address and Phone_Number.
    Cust_Code Name, Address, Phone_Number
  • 9. Steps in Normalization
    Boyce -Codd NF, 4 NF and 5NF
    3 NF
    2 NF
    1 NF
    Unnormalized Relation
  • 10. Steps in Normalization
    1NF: A relation is in 1NF if multi-valued attributes (also called repeating groups) have been removed, so there is a single value (possibly null) at the intersection of each row and column of the table.
    2NF: A relation is in 2NF if it is in 1NF, and contains no partial dependencies.
    A partial functional dependency in a relation is a functional dependency in which one or more nonkey attributes are functionally dependent on part (but not all) of the primary key.
    3NF:Arelation is in 3NF if it is in 2NF and no transitive dependencies exist.
    A transitive dependency in a relation is a functional dependency between two (or more) nonkey attributes.
  • 11. Pine Valley Furniture Company Database
  • 12. Invoice Data - Pine Valley Furniture Company
  • 13. 1 NF: A relation is in 1NF if multi-valued attributes (also called repeating groups) have been removed, so there is a single value (possibly null) at the intersection of each row and column of the table.
  • 14. Functional Dependency Diagram for Invoice
    A partial functional dependency in a relation is a functional dependency in which one or more nonkey attributes are functionally dependent on part (but not all) of the primary key.
  • 15. Removing Partial Dependencies
    2NF: A relation is in 2NF if it is in 1NF, and contains no partial dependencies.
    A transitive dependency in a relation is a functional dependency between two (or more) nonkey attributes.
  • 16. Removing Transitive Dependencies
    3NF:Arelation is in 3NF if it is in 2NF and no transitive dependencies exist.
  • 17. Relational Scheme for INVOICE data(MS Visio)
    Note to Students: For drawing ER diagram of your project , Try MS Visio, an easy to use tool to draw the ER Diagram as one shown above
  • 18. SQL – Structured Query Language
    SQL Statements
    SELECT (select list)
    FROM (table List)
    WHERE (condition for
    retrieval)
    ORDER BY (sort criteria)
    Example:
    SELECT Empno, Ename,
    Job, Sal
    FROM EMP
    WHERESal > 2500
    ORDER BY Job, Ename
    Table : EMP
    EmpnoEname Job Sal
    8756 Dravid President 8000
    5348 Raju Manager 5000
  • 19. SQL – Structured Query Language
    SQL Statements
    SELECT (select list)
    FROM (table List)
    WHERE (condition for
    retrieval)
    ORDER BY (sort criteria)
    Example:
    SELECT Order Number, Unit Price *Quantity AS Total
    FROM Order
  • 20. Normalization - Recap
  • 21. SUMMARY - Normalization – Rules – 1NF TO 3NF
    1NF: A relation is in 1NF if multi-valued attributes (also called repeating groups) have been removed, so there is a single value (possibly null) at the intersection of each row and column of the table.
    2NF: A relation is in 2NF if it is in 1NF, and contains no partial dependencies.
    A partial functional dependency in a relation is a functional dependency in which one or more nonkey attributes are functionally dependent on part (but not all) of the primary key.
    3NF:Arelation is in 3NF if it is in 2NF and no transitive dependencies exist.
    A transitive dependency in a relation is a functional dependency between two (or more) nonkey attributes.
  • 22. SUMMARY - Normalization – Rules – 1NF TO 3NF
    Second Normal Form (2NF)
    Second normal form (2NF) further addresses the concept of removing duplicative data:
    Meet all the requirements of the first normal form.
    Remove subsets of data that apply to multiple rows of a table and place them in separate tables.
    Create relationships between these new tables and their predecessors through the use of foreign keys.
    First Normal Form (1NF)
    First normal form (1NF) sets the very basic rules for an organized database:
    Eliminate duplicative columns from the same table.
    Create separate tables for each group of related data and identify each row with a unique column or set of columns (the primary key).
    Third Normal Form (3NF)
    • Third normal form (3NF) goes one large step further:
    • 23. Meet all the requirements of the second normal form.
    • 24. Remove columns that are not dependent upon the primary key.
  • 1NF
    Eliminate Repeating Groups - Make a separate table for each set of related attributes, and give each table a primary key.
    2NF
    Eliminate Redundant Data - If an attribute depends on only part of a multi-valued key, remove it to a separate table.
    3NF
    Eliminate Columns Not Dependent On Key - If attributes do not contribute to a description of the key, remove them to a separate table.
    SUMMARY - Normalization – Rules – 1NF TO 3NF
  • 25. Normalization - Exercises
  • 26. Normalize
  • 27. Normalize
    Exercise 1
    Emp _No
    Prof_Designation
    Emp_Name
    Dept_Code
    Dept_Name
    Prof_Office
    Student_Name
    Student_Id
    Student DOB
    Student Age
    Exercise 2
    Prod No
    Prod Desc
    Item No
    Salesperson Name
    Customer Name
    Quantity
    Price
  • 28. Normalize
    Emp No
    Emp Name
    Dept No
    Dept Name
    Mgr No
    Proj No
    Proj Name
    Start Date
    Billing Rate
  • 29. Normalize