Normalization
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    Normalization Normalization Presentation Transcript

    • NORMALIZATION Rajishma T rajishmatnair@gmail.com www.facebook.com/ Rajishma T Nair twitter.com/username in.linkedin.com/in/profilena me 9020217968
    • Disclaimer: This presentation is prepared by trainees of baabtra as a part of mentoring program. This is not official document of baabtra –Mentoring Partner Baabtra-Mentoring Partner is the mentoring division of baabte System Technologies Pvt . Ltd
    • NORMALIZATION  Normalization is the process of removing potential anomalies from the database design. These anomalies include: – Insertion anomalies – Update anomalies – Deletion anomalies
    • INSERTION ANOMALIES An insertion anomaly occurs when you can’t enter a record in because some data is missing. Consider a database with the rule that every employee must be assigned to a project, but a newly hired employee doesn’t have a project yet. One solution is to create a dummy project, but this puts bad data into your database and is not a good idea.
    • UPDATE ANOMALIES  Update anomalies occur when the same data is stored in more than one place.  This means whenever you have to make a change to the data, you must do it in several places.  The more times you have to edit the same data in multiple places, the more chances you have of making a mistake, causing inconsistent data.
    • DELETION ANOMALIES causes other data to be lost Deletion anomalies occur when deleting a record accidently .
    •  Normalization: – The process of decomposing unsatisfactory "bad" relations by breaking up their attributes into smaller relations  Normal form: – Condition using keys and FDs of a relation to certify whether a relation schema is in a particular normal form
    • FIRST NORMAL FORM  Only attribute values permitted are single atomic (or indivisible) values Techniques to achieve first normal form – Remove attribute and place in separate relation – Expand the key – Use several atomic attributes
    • SECOND NORMAL FORM  Second Normal Form removes what are called “functional dependencies.”  Functional dependencies are groups of columns that depend on each other rather than on the key of the table.
    •  Functional dependencies (FDs) – Are used to specify formal measures of the "goodness" of relational designs – And keys are used to define normal forms for relations – Are constraints that are derived from the meaning and interrelationships of the data attributes  A set of attributes x functionally depends a set of attributes Y if the value of X determines a unique value for Y
    •  X -> Y holds if whenever two tuples have the same valuefor X, they must have the same value for Y – For any two tuples t1 and t2 in any relation instance r(R): If t1[X]=t2[X], then t1[Y]=t2[Y]  X -> Y in R specifies a constraint on all relation instances r(R)
    • SECOND NORMAL FORM  Formal definition of 2NF is a table that is in 1NF and every non-primary-key column is fully functional dependent on the primary key.  Full functional dependency indicates that if A and B are columns of a table, B is fully dependent on A if B is functionally dependent on A but not on any proper subset of A.
    • TRANSITIONAL DEPENDENCY  Transitive functional dependency: a FD X -> Z that can be derived from two FDs X -> Y and Y -> Z  For example, consider a table with A, B, and C. If B is functional dependent on A and C is functional dependent on B , then C is transitively dependent on A via B (provided that A is not functionally dependent on B or C).  If a transitive dependency exists on the primary key, the table is not in 3NF. `
    • BCNF A relation R is in Boyce/Codd N/F (BCNF) if and only if every determinant is a candidate key. Here, determinant is a simple attribute or composite attribute on which some other attributes is fully functionally dependent. Each normal form is strictly stronger than the previous one Every 2NF relation is in 1NF Every 3NF relation is in 2NF Every BCNF relation is in 3NF  There exist relations that are in 3NF but not in BCNF  The goal is to have each relation in BCNF (or 3NF)
    • campus course class time Room/bldng east English 101 1 8:00-9:00 212 AYE east English 101 2 10:00-11:00 305 RFK West English 101 3 8:00-9:00 102 PPR
    • • no two buildings on any of the university campuses have the same name, thus ROOM/BLDG----- >CAMPUS. As the determinant is not a candidate key this table is not in bcnf. • R1(course, class, room/bldg, time) • course class time Room/bldng English 101 1 8:00-9:00 212 AYE English 101 2 10:00-11:00 305RFK English 101 3 8:00-9:00 102PPR
    • • R2(room/bldg, campus) campus Room/bldng east 212 AYE east 305 RFK west 102 PPR
    • Identify all candidate keys in the relation. Identify all functional dependencies in the relation. If functional dependencies exists in the relation where their determinants are not candidate keys for the relation, remove the functional dependencies by placing them in a new relation along with a copy of their determinant.
    • FOURTH NORMAL FORM 4NF: A relation that is in Boyce-Codd Normal Form and contains no MVDs. BCNF to 4NF involves the removal of the MVD from the relation by placing the attribute(s) in a new relation along with a copy of the determinant
    • MVD multi-valued dependency • Represents a dependency between attributes (for example, A, B, and C) in a relation, such that for each value of A there is a set of values for B, and a set of values for C. However, the set of values for B and C are independent of each other
    • 50 Normalization BCNF to 4NF Relations
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