INFO 340 Lecture 7 Functional Dependency, Normalization

DeMorgan’s Theorem A AND B = A OR B A OR B = A AND B

“Spreadsheet Syndrome” When you use a spreadsheet program, you only really have one table. This leads to duplication of data.

Normalization Goal: Every non-key column is directly dependent on the key, the whole key, and nothing but the key Goal: Reduce redundancies, less anomalies, and improve efficiency.

Data Redundancy & Update Anomalies Insertion Anomaly – Staff # | sName | position | salary | branch# | bAddress Add new staff & bAddress must be updated also – creating opportunity for error Want to add new branch w/no staff means we have to enter nulls for staff members Deletion Anomaly Deleting last staff member of a branch also deletes details on branch Modification Anomaly Updating details of a particular branch must be done for all rows – creating opportunity for error

Functional Dependency & Normalization How to identify the most commonly used normal forms, namely First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF).

What happens if normalization hasn’t occurred? Data duplication Multiple truths Difficulty to query

Full functional dependency A fully functional dependency is when you can not remove items from the first set (the A in A  B) and maintain a functional dependency.

Transitive Dependency Transitive dependency describes a condition where A, B, and C are attributes of a relation such that if A → B and B → C, then C is transitively dependent on A via B (provided that A is not functionally dependent on B or C).

Functional Dependency & Normalization Main characteristics of functional dependencies used in normalization: – There is a one-to-one relationship between the attribute(s) on the left-hand side (determinant) and those on the right-hand side of a functional dependency. – Holds for all time. – The determinant has the minimal number of attributes necessary to maintain the dependency with the attribute(s) on the right hand-side.

Normalization Formal technique for analyzing a relation based on its primary key and the functional dependencies between the attributes of that relation. Formal method to cross-check your work – “sanity check” Often executed as a series of steps. Each step corresponds to a specific normal form, which has known properties. As normalization proceeds, the relations become progressively more restricted (stronger) in format and also less vulnerable to update anomalies.

1 st Normalized Form A relation in which the intersection of each row and column contains one and only one value. Atomicity. Based upon you’re requirements, a column holds only one value.

2 nd Normal Form Based on the concept of full functional dependency. A relation that is in 1NF and every non- primary-key attribute is fully functionally dependent on the primary key.

2NF examples StudentClassLocation JohnCSE 143EEB 103 JohnEE 131EEB 103 SusieINFO 340MGH 238 SusieMATH 124PAR 104 SusieEE 131EEB 103 While in 1NF form, it is not in 2NF form. Candidate Key {Student,Class}. Location is not fully functional dependent, since it is dependent only on Class. StudentClass JohnCSE 143 JohnEE 131 SusieINFO 340 SusieMATH 124 SusieEE 131 ClassLocation CSE 143EEB 103 EE 131EEB 103 INFO 340MGH 238 MATH 124 PAR 104

3 rd Normal Form Based on the concept of transitive dependency. A relation that is in 1NF and 2NF and in which no non-primary-key attribute is transitively dependent on the primary key.

3NF example PublisherIDNameAddressCityStateZIP 1Apress2560 Ninth Street, Station 219BerkeleyCA94710 Looks good, but notice that City and State are really dependent on ZIP, not Publisher_ID. A good way to find transitive functional dependencies is think to yourself. – “If I update this column, do I need to update others?” In this case, updating the City column would require you to update the ZIP and possible the State column. This example, though, hints that one of the dangers of normalization, that you can sometimes go too far.. PublisherIDNameAddressZIP 1Apress2560 Ninth Street, Station ZIPCityState 94710BerkeleyCA

MidTerm Overview Limitations of file-based systems Difference in a DDL & DML Advantages/disadvantages of DBMS’s Differences in External, Conceptual, & Internal levels of DBMS’s Data independence Functions of a DBMS Relation, attribute, domain,cardinality, degree Attribute domains Cartesian product Properties of a relation Keys – super, candidate, primary, foreign Null Entity integrity, referential integrity Sets – union, intersection, difference Joins – inner, right outer, left outer SQL – selects, updates, inserts, aggregates, group by, order by Wild cards Nested query DeMorgan’s Theorem in an SQL query Relational algebra – difference between a selection & a projection Entity relationship diagrams Mulitplicity Functional dependency Definitions of First, Second, & Third Normal form Be able to identify if a relation is in 1NF, 2NF, or 3NF Difference between Integer types in MySQL

Homework Complete Mini-Project work Prepare for mid-term