Normalization is a process of reducing a relation to
Normalization should be part of the database design process. However, it is difficult to separate the normalization process from the ER modelling process so the two techniques should be used concurrently. Show
Use an entity relation diagram (ERD) to provide the big picture, or macro view, of an organization’s data requirements and operations. This is created through an iterative process that involves identifying relevant entities, their attributes and their relationships. Normalization procedure focuses on characteristics of specific entities and represents the micro view of entities within the ERD. What Is Normalization?Normalization is the branch of relational theory that provides design insights. It is the process of determining how much redundancy exists in a table. The goals of normalization are to:
Normalization theory draws heavily on the theory of functional dependencies. Normalization theory defines six normal forms (NF). Each normal form involves a set of dependency properties that a schema must satisfy and each normal form gives guarantees about the presence and/or absence of update anomalies. This means that higher normal forms have less redundancy, and as a result, fewer update problems. Normal FormsAll the tables in any database can be in one of the normal forms we will discuss next. Ideally we only want minimal redundancy for PK to FK. Everything else should be derived from other tables. There are six normal forms, but we will only look at the first four, which are:
BCNF is rarely used. First Normal Form (1NF)In the first normal form, only single values are permitted at the intersection of each row and column; hence, there are no repeating groups. To normalize a relation that contains a repeating group, remove the repeating group and form two new relations. The PK of the new relation is a combination of the PK of the original relation plus an attribute from the newly created relation for unique identification. Process for 1NFWe will use the Student_Grade_Report table below, from a School database, as our example to explain the process for 1NF. Student_Grade_Report (StudentNo, StudentName, Major, CourseNo, CourseName, InstructorNo, InstructorName, InstructorLocation, Grade)
Student (StudentNo, StudentName, Major) StudentCourse (StudentNo, CourseNo, CourseName, InstructorNo, InstructorName, InstructorLocation, Grade) How to update 1NF anomaliesStudentCourse (StudentNo, CourseNo, CourseName, InstructorNo, InstructorName, InstructorLocation, Grade)
Second Normal Form (2NF)For the second normal form, the relation must first be in 1NF. The relation is automatically in 2NF if, and only if, the PK comprises a single attribute. If the relation has a composite PK, then each non-key attribute must be fully dependent on the entire PK and not on a subset of the PK (i.e., there must be no partial dependency or augmentation). Process for 2NFTo move to 2NF, a table must first be in 1NF.
Student (StudentNo, StudentName, Major) CourseGrade (StudentNo, CourseNo, Grade) CourseInstructor (CourseNo, CourseName, InstructorNo, InstructorName, InstructorLocation) How to update 2NF anomalies
Third Normal Form (3NF)To be in third normal form, the relation must be in second normal form. Also all transitive dependencies must be removed; a non-key attribute may not be functionally dependent on another non-key attribute. Process for 3NF
Student (StudentNo, StudentName, Major) CourseGrade (StudentNo, CourseNo, Grade) Course (CourseNo, CourseName, InstructorNo) Instructor (InstructorNo, InstructorName, InstructorLocation) At this stage, there should be no anomalies in third normal form. Let’s look at the dependency diagram (Figure 12.1) for this example. The first step is to remove repeating groups, as discussed above. Student (StudentNo, StudentName, Major) StudentCourse (StudentNo, CourseNo, CourseName, InstructorNo, InstructorName, InstructorLocation, Grade) To recap the normalization process for the School database, review the dependencies shown in Figure 12.1. Figure 12.1 Dependency diagram, by A. Watt.The abbreviations used in Figure 12.1 are as follows:
Boyce-Codd Normal Form (BCNF)When a table has more than one candidate key, anomalies may result even though the relation is in 3NF. Boyce-Codd normal form is a special case of 3NF. A relation is in BCNF if, and only if, every determinant is a candidate key. BCNF Example 1Consider the following table (St_Maj_Adv). Student_idMajorAdvisor111PhysicsSmith111MusicChan320MathDobbs671PhysicsWhite803PhysicsSmithThe semantic rules (business rules applied to the database) for this table are:
The functional dependencies for this table are listed below. The first one is a candidate key; the second is not.
Anomalies for this table include:
Note: No single attribute is a candidate key. PK can be Student_id, Major or Student_id, Advisor. To reduce the St_Maj_Adv relation to BCNF, you create two new tables:
St_Adv table Student_idAdvisor111Smith111Chan320Dobbs671White803SmithAdv_Maj table BCNF Example 2Consider the following table (Client_Interview). ClientNoInterviewDateInterviewTimeStaffNoRoomNoCR7613-May-0210.30SG5G101CR5613-May-0212.00SG5G101CR7413-May-0212.00SG37G102CR561-July-0210.30SG5G102FD1 – ClientNo, InterviewDate –> InterviewTime, StaffNo, RoomNo (PK) FD2 – staffNo, interviewDate, interviewTime –> clientNO (candidate key: CK) FD3 – roomNo, interviewDate, interviewTime –> staffNo, clientNo (CK) FD4 – staffNo, interviewDate –> roomNo A relation is in BCNF if, and only if, every determinant is a candidate key. We need to create a table that incorporates the first three FDs (Client_Interview2 table) and another table (StaffRoom table) for the fourth FD. Client_Interview2 table StaffRoom table StaffNoInterviewDateRoomNoSG513-May-02G101SG3713-May-02G102SG51-July-02G102Normalization and Database DesignDuring the normalization process of database design, make sure that proposed entities meet required normal form before table structures are created. Many real-world databases have been improperly designed or burdened with anomalies if improperly modified during the course of time. You may be asked to redesign and modify existing databases. This can be a large undertaking if the tables are not properly normalized. Boyce-Codd normal form (BCNF): a special case of 3rd NF first normal form (1NF): only single values are permitted at the intersection of each row and column so there are no repeating groups normalization: the process of determining how much redundancy exists in a table second normal form (2NF): the relation must be in 1NF and the PK comprises a single attribute semantic rules: business rules applied to the database third normal form (3NF): the relation must be in 2NF and all transitive dependencies must be removed; a non-key attribute may not be functionally dependent on another non-key attribute Complete chapters 11 and 12 before doing these exercises.
Also see Appendix B: Sample ERD Exercises BibliographyNguyen Kim Anh, Relational Design Theory. OpenStax CNX. 8 Jul 2009 Retrieved July 2014 from http://cnx.org/contents/606cc532-0b1d-419d-a0ec-ac4e2e2d533b@1@1 Russell, Gordon. Chapter 4 – Normalisation. Database eLearning. N.d. Retrived July 2014 from db.grussell.org/ch4.html What is the main goal of normalization process?There are two main objectives of the normalization process: eliminate redundant data (storing the same data in more than one table) and ensure data dependencies make sense (only storing related data in a table).
Does normalization reduce number of tables?Normalization increases the number of tables and joins. In contrast, denormalization reduces the number of tables and join. Disk space is wasted in denormalization because same data is stored in different places. On the contrary, disk space is optimized in a normalized table.
What is a normalized relation?if two countries normalize relations, they have a friendly relationship again after a war or disagreement. The United States has decided to normalize relations with Vietnam. Synonyms and related words.
Does normalization reduce data?Normalization is the process of reducing data redundancy in a table and improving data integrity.
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