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Data Modeling
- 1. DATABASE DESIGN: DATAMODELING AND NORMALIZATION Dr. R. Khanchana Assistant Professor Department of Computer Science Sri Ramakrishna College of Arts and Science for Women
- 2. Data Modeling Data Modeling: •Data modeling - A tool used to represent various components and their relationships. • Popular modeling tool is Entity Relational Model(E-R Model) • E-R Model provides An excellent communication tools A simple graphical representation of data. • E-R Model uses E-R Diagram(ERD) for graphical representation of the database components. • An entity is represented by a rectangle it uses upper case letters and it should be singular noun Eg. EMPLOYEE,DEPARTMENT etc • Entity Representation in an E-R Diagram EMPLOYEE
- 3. Representation of Relationship •The line represents the relationship between the two entities it uses lowercase letters and it should be active verb • Passive verb can be used but active verb is preferable. • Representation of relationship in an E-R diagram 1:1 • The types of relationships (1:1,1:M,M:N) between entities are called connectivity or multiplicity. M: N 1: Mmanages employs contains
- 4. Entity, Relationship, Connectivity •The types of relationships (1:1,1:M,M:N) between entities are called Connectivity or Multiplicity • The connectivity is shown with vertical or angled lines next to each entity
- 5. Cardinality • The Relationshipbetween two entities can be given suing the lowercase and uppercase limits • Example - (n,m) • n – lower limit • m – upper limit DEPARTMENTEMPLOYEE FACULTYDIVISION ITEMINVOICE Supervises Employees Contains (1, 1) (1, 1) (1, N) (1, 1) (1, N) (1, N)
- 6. Data Model BasicBuilding Blocks
- 7. Cardinality Types • Ithas 2 types – Mandatory Relationship – Optional Relationship • Oracle set rules for the minimum and maximum values for cardinality. These types of decision are known as business rules.
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- 10. Optional Relationship • Optionalrelationships are shown with a small circle next to the optional entity. • The optional relational relationship can occur in 1:1,1:M or M:N relationships and it can occur on one or both sides of the relationship. • In relational databases many-to-many (M:N) relationships are allowed but they are not easy to implement.
- 11. Composite Entity &Relational Schema • The decomposition from M:N to1:M involves a third entity and it is known as Composition entity or Associative entity
- 12. Weak Entity • Thereare entities that cannot exist by themselves.
- 13. Other Elements • Someof the other elements considered in the database design are Simple Attributes: Attributes that cannot be subdivided Eg. city, gender Composite Attributes: Attributes that can be subdivided Eg. Full name(Last name, First name, Middle Initial) Single valued Attributes: Attributes with a single value Eg. Employee Id, Student Id Multivalued Attributes: Attributes with multiple values Eg. Course details
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- 15. Dependency • A dependencyis a constraint that applies to or defines the relationship between attributes. • Primary key which uniquely identifies an entity • The column that do not make up the primary key for the table such columns are called the nonkey column • The non key columns are functionally dependent on the primary key columns • There are three types of dependency in tables – Total or full dependency: A nonkey column dependent on all primary key column – Partial dependency : A nonkey column is dependent on part of the primary key – Transitive dependency :A nonkey column is dependent on another nonkey column.
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- 18. Normal forms • Redundancy- Data Repetition • Anomaly (Data Inconsistency) • – if a change in piece of data, the change has to made in many places
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- 20. Deletion Anomaly • Whichresults when the deletion of information about one entity leads to the deletion of another entity. • If someone decides to delete Botany department , he may end up deleting all student’s data who had the department of Botany.
- 21. Insertion Anomaly When theinformation about an entity cannot be inserted unless the information about another entity is known and it is said to be Insertion Anomaly Jerry is a new Student with department id 6. There is no Department with this Dept_ID 6. Hence , the anomaly. The usual behaviour should be a new department id with 6 and only then Student could have it.
- 22. Update Anomaly • Anupdate anomaly occurs when data is only partially updated in a database. • English department has now Dept_ID 8 , but unfortunately it was not updated in Student table.
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- 25. Normalization • Normalization isthe process of organizing the data in the database. • Normalization is used to minimize the redundancy from a relation or set of relations. • Normalization divides the larger table into the smaller table and links them using relationship. • The normal form is used to reduce redundancy from the database table.
- 26. Review • Data Modeling –Entity – Attribute – Connectivity – Cardinality -Notation • Dependency • Database design
- 27. Types of NormalForms • Higher Normal Form - Lower the redundancy i) First Normal Form(1NF) ii) Second Normal Form(2NF) iii) Third Normal Form(3NF)
- 28. First Normal Form(1NF) The table said to be first normal form (or) labeled 1NF if the following conditions exists: • The primary key is defined • Also includes composite key if a single column cannot be used as a primary key. • First normal form disallows the multi-valued attribute/ composite attribute, and their combinations. Example: Relation EMPLOYEE is not in 1NF because of multi-valued attribute EMP_PHONE
- 29. Second Normal Form(2NF) • All 1NF requirements are fulfilled •No partial dependency •Suppose the table is in 1NF and does not have composite key and it is said to be 2NF. Example: A school can store the data of teachers and the subjects they teach. In a school, a teacher can teach more than one subject.
- 30. Second Normal Form(2NF)
- 31. Third Normal Form(3NF) • Table is said to be third normal form (or) 3NF if the following requirements are satisfied. – All 2NF requirements are fulfilled. – No transitive dependency- non key column is dependent on another non key column.
- 32. Third Normal Form(3NF) • Super key in the table above: – {EMP_ID}, {EMP_ID, EMP_NAME}, {EMP_ID, EMP_NAME, EMP_ZIP}....so on • Candidate key: {EMP_ID} • Non-prime attributes: all attributes except EMP_ID are non-prime. – EMP_STATE & EMP_CITY dependent on EMP_ZIP and EMP_ZIP dependent on EMP_ID. – The non-prime attributes (EMP_STATE, EMP_CITY) transitively dependent on super key(EMP_ID). It violates the rule of third normal form. – Hence need to move the EMP_CITY and EMP_STATE to the new <EMPLOYEE_ZIP> table, with EMP_ZIP as a Primary key.
- 33. Third Normal Form(3NF)
- 34. Other Normal forms •BCNF - BoyceCodd Normal Form(BCNF) • 4NF –Fourth Normal Form • 5NF - Fifth Normal Form • DKNF –Domain Key Normal Form
- 35. Dependency Diagram • Totaldependencies arrows are drawn above the boxes. • Partial & transitive dependencies arrows are drawn below the boxes. • i)Conversion from 1NF to 2NF • ii)Conversion from 2NF to 3NF
- 36. Conversion from 1NFto 2NF • The composite primary key is in the table remove partial dependency. • 1st each primary key component on a separate line , they will become primary key in two new tables. • Composite key on the third line it will be the composite key on the third table. 1NF to 2NF Decomposition
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- 38. Conversion from 2NFto 3NF • Invoice table still has transitive dependency but no partial dependency. • More columns of transitive dependency to a new table. • Keep the primary key of new table as a foreign key at existing table. 2NF to 3NF Decomposition
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- 40. Denormaization • Normalization process- splits tables into smaller tables • Smaller tables are joined together by common columns to retrieve information from different tables. • Denomalization process – reverse process • It reduces normal form and increases data redundancy • Duplicate data are stored more storage space is required
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- 43. Assignment –Case Study •Assume, a video library maintains a database of movies rented out. Without any normalization, all information is stored in one table as shown below.
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