UNIT II DBMS.pptx
- 2. • Entity-Relationship model - E-R Diagrams - Reduction to Relational Schema - Extended E- R Features - Atomic Domains and First Normal Form - Decomposition using Functional Dependencies - Functional Dependency Theory - Algorithm for Decomposition - Decomposition using Multi- Valued Dependencies- More Normal Forms.
- 3. Entity-Relationship model E-R diagram can express the overall logical structure of a database graphically It develops a conceptual design for the database. It also develops a very simple and easy to design view of data. It is easy to visualize and understand.
- 4. The E-R data model employs three basic concepts: Entity sets Relationship sets and Attributes
- 5. Entity set Entity: - a “thing” or “object” in the real world that is distinguishable from all other objects. An entity has a set of properties, and the values for some set of properties must uniquely identify an entity For example, in a school database, students, teachers, classes, and courses offered can be considered as entities..
- 6. Entity Set: An entity set is a collection of similar types of entities. An entity set may contain entities with attribute sharing similar values. For example, the entity set “student” might represent the set of all students in the university. Entity
- 7. Attributes Entities are represented by means of their properties, called attributes. All attributes have values. For example, a student entity may have name, class, and age as attributes.
- 8. Types of Attributes: 1) Simple attribute − Simple attributes are atomic values, which cannot be divided further. For example, a student's phone number is an atomic value of 10 digits. 2) Composite attribute − Composite attributes are made of more than one simple attribute. For example, a student's complete name may have first_name and last_name.
- 9. 3) Derived attribute : Derived attributes are the attributes that do not exist in the physical database, but their values are derived from other attributes present in the database. For example, average_salary in a department should not be saved directly in the database, instead it can be derived. For another example, age can be derived from data_of_birth.
- 10. 3) Single-value attribute Single-value attributes contain single value. Ex: name, id 4) Multi-value attribute Multi-value attributes may contain more than one values. For example, a person can have more than one phone number, email_address, etc.
- 11. Entity-Set and Keys Key is an attribute or collection of attributes that uniquely identifies an entity among entity set. For example, the roll_number of a student identifiable among students. Super Key − A set of attributes (one or more) that collectively identifies an entity in an entity set. Candidate Key − A minimal super key is called a candidate key. An entity set may have more than one candidate key. Primary Key − A primary key is one of the candidate keys chosen by the database designer to uniquely identify the entity set.
- 12. Relationship The association among entities is called a relationship. For example, an employee works_at a department, a student enrolls in a course. Here, Works_at and Enrolls are called relationships. In ER diagram, relationship type is represented by a diamond and connecting the entities with lines.
- 13. Degree of a relationship set: The number of different entity sets participating in a relationship set is called as degree of a relationship set. 1) Unary Relationship – When there is only ONE entity set participating in a relation, the relationship is called as unary relationship. For example, one person is married to only one person.
- 14. 2) Binary Relationship (degree 2) When there are TWO entities set participating in a relation, the relationship is called as binary relationship. For example, Student is enrolled in Course. 3) Ternary (degree 3) In the Ternary relationship, there are three types of entity associates.
- 15. 4) n-ary Relationship When there are n entities set participating in a relation, the relationship is called as n-ary relationship. We have 5 entities Teacher, Class, Location, Salary, Course. So, here five entity types are associating we can say an n- ary relationship is 5.
- 16. Cardinality/Constrains Cardinality is the number of instance of an entity from a relation that can be associated with the relation. 1) One to One Relationship When only one instance of an entity is associated with the relationship, it is marked as '1:1'.
- 17. 2) One-to-many When more than one instance of an entity is associated with a relationship, it is marked as '1:N'.
- 18. 3) Many-to-one When more than one instance of entity is associated with the relationship, it is marked as 'N:1'.
- 19. Many – to - Many When more than one instances of an entity is associated with more than one instances of another entity then it is called many to many relationship.
- 20. Participation Constraints Total Participation − Each entity is involved in the relationship. Total participation is represented by double lines. Partial participation − Not all entities are involved in the relationship. Partial participation is represented by single lines.
- 21. Strong Entity: The strong entity has a primary key. Weak entities are dependent on strong entity. Its existence is not dependent on any other entity. Strong Entity is represented by a single rectangle − Weak Entity: The weak entity in DBMS do not have a primary key and are dependent on the parent entity. It mainly depends on other entities. Weak Entity is represented by double rectangle −
- 22. Your Text Here
- 26. Normalization A technique of organizing the data into multiple related tables, to minimize Data Redundancy “Good Database”
- 27. Normalization is the process of organizing the data in the database. Normalization is used to minimize the redundancy from a relation or set of relations. It is also used to eliminate undesirable characteristics like Insertion, Update, and Deletion Anomalies. Normalization divides the larger table into smaller and links them using relationships.
- 28. Data Redundancy Repetition of data, increases the size of database Other issues like: Insertion problems Deletion problems Updation problems
- 31. Atomic Domain and 1st Normal Form "Atomic" means "cannot be divided or split in smaller parts". Applied to 1NF this means that a column should not contain more than one value. Step 1 of Normalization: Scalable Table design which can be easily extensible. If our Table not even in 1st Normal form its considered a poor Database.
- 33. 4 RULES Rule 1: Each Column should have atomic values
- 35. 4 RULES Rule 2: A Column should contain values that are of same type Do not inter-mix different types of values in any column
- 36. 4 RULES Rule 3: Each column should have a unique name
- 37. 4 RULES Rule 4: Order in which data is doesn’t matter. Using SQL query you can easily fetch data in any order from the table
- 38. 2nd Normal Form(2NF) For a table to be in the Second Normal Form, it must satisfy two conditions: The table should be in the First Normal Form. There should be no Partial Dependency.
- 39. Prime Attribute & Non-Prime Attribute
- 40. Functional Dependency Functional dependency is a relationship of one attribute or field in a record to another. In DB, we often have the case where one field defines the other. “X determines Y” or “ X is Functionally dependent on Y” Marks Grade X Y It typically exists between the primary key and non- key attribute within a table.
- 41. StudentID ProjectID StudentName ProjectName S89 P09 Olivia Geo Location S92 P07 Alexandra Cluster Exploration S56 P03 Ava IoT Devices S92 P05 Alexandra Cloud Deployment ProjectID ProjectName Primary key
- 42. {Student ID, ProjectID} Primary key StudentID ProjectID StudentName ProjectName S89 P09 Olivia Geo Location S76 P07 Jacob Cluster Exploration S56 P03 Ava IoT Devices S92 P05 Alexandra Cloud Deployment
- 44. {Student ID, Subject ID} Primary key
- 45. Teacher column only depends on subjectid
- 48. {Employee ID, Department ID} Primary key
- 50. 3rd Normal Form(3NF) A relation will be in 3NF if it is in 2NF and not contain any transitive partial dependency
- 52. Primary key or prime attribute
- 58. X Y Prime attribute Non- Prime attribute Functional Dependency X Y Part of Prime attribute Non- Prime attribute Partial Functional Dependency
- 59. X Y Non - prime attribute Non- Prime attribute X Y SUPER KEY BCNF Trasitive Functional Dependency
- 60. Boyce codd Normal Form(BCNF) OR 3.5 Normal Form It should be in 3rd Normal form For any dependency X Y, X must be in super Key
- 62. Professor Subject Not a super key
- 64. 4TH NORMAL FORM(4NF) 1)A relation will be in 4NF if it is in Boyce Codd normal form 2)no multi-valued dependency.
- 65. For a dependency A → B, if for a single value of A, multiple values of B exists, then the relation will be a multi-valued dependency.
- 67. For a table with A,B,C columns A B , is Multi Valued Dependency Then B and C should be independent of each other Three Rules of Multi Valued Dependency:
- 69. A table is said to be in Fifth Normal Form if it satisfies the following properties 1.If it is in fourth normal form and 2.It should not have join dependency It is also called as Project Join Normal Form(PJNF) If the table is having join dependency then it should be broken into smaller tables. 5th Normal Form(5NF)
- 70. R R1 R2 R A relation with join dependency Break down Join again Get the same relation again
- 71. AGENT COMPANY PRODUCT A CAR A TRUCK A CAR A TRUCK B CAR
- 72. AGENT COMPANY PRODUCT A FORD CAR A FORD TRUCK A GM CAR A GM TRUCK B FORD CAR
- 73. AGENT COMPANY A FORD A GM B FORD COMPANY PRODUCT FORD CAR FORD TRUCK GM CAR GM TRUCK AGENT PRODUCT A CAR A TRUCK B CAR R1 R2 R3
- 74. AGENT COMPANY A FORD A GM B FORD COMPA NY PRODU CT FORD CAR FORD TRUCK GM CAR GM TRUCK AGENT PRODUCT A CAR A TRUCK B CAR AGENT COMPANY PRODUCT A FORD CAR A FORD TRUCK A GM CAR A GM TRUCK B FORD CAR