1. Brian Thoms

2.  Databases normalization The systematic way of ensuring that a database structure is suitable for general-purpose querying and free of certain undesirable characteristics. But what does that mean? 2

3.  ERD Macro view of an organization’s requirements and operations Can be transformed to DB design using iterative process  DB Normalization Micro view of entities (and their attributes) 3

4.  Reduce unnecessary redundancy since too much redundancy across tables will generate anomalies  But the goal is not to eliminate all redundancy (some redundancy is desirable)  Trade-off: Normalization does not mean better Data becomes spread across a larger number of tables (i.e. more normalization  more joins)  Types: 1NF, 2NF, 3NF, BCNF, 4NF (and, theoretically, higher forms exist 5NF / 6NF) 4

5.  Why do we normalize? Data can suffer from logical inconsistencies from operations involving data updates, insertions, and deletions (aka data anomalies). 5 Update Anomaly The same information can be expressed on multiple records; therefore updates to the table may result in logical inconsistencies. (e.g.) employee 519 changes his/her address requiring changes across multiple tables/records?

6. Insertion Anomaly Circumstances in which certain facts cannot be recorded at all. (e.g.) A new faculty member arrives but has not been assigned any courses to teach therefore blanks/null data must be entered? Deletion Anomaly Circumstances when deleting of data representing certain facts requires the deletion of data representing completely different facts. (e.g.) Deleting a course taught for a faculty member could deletes the entire record for that faculty member. 6

7.  First Normal Form (1NF)  Second Normal Form (2NF)  Third Normal Form (3NF)  Boyce-Codd Normal Form (BCNF)  Fourth Normal form (4NF)  (Theoretical) Fifth Normal Form (5NF)  (Theoretical) Sixth Normal Form (6NF) 7

8.  1NF Table faithfully represents a relation and has no "repeating groups“ (i.e. columns with-in/across that store the same data). 8

9.  2NF A table is 1NF No non-prime attribute in the table is functionally dependent on a part (proper subset) of a candidate key (i.e. no partial dependencies exist). 9 +

10.  3NF A table is 2NF Every non-prime attribute is non-transitively dependent on every key of the table. 10 + DoB is dependent on Winner?

11.  (Informally) A relational database table is described as "normalized" if it is in 3NF.  Most 3NF tables are free of insertion, update, and deletion anomalies. 11

12.  BCNF Every non-trivial functional dependency is dependent on a candidate key. BCNF is violated if the table contains more than 1 candidate key. Only in rare cases does a 3NF table not meet the requirements of BCNF 12 (Saver should always be on Court 1)

13.  4NF Table is in 3NF. No multivalued dependencies exist.  Multivalued dependencies occur when a determinant determines a particular set of values (e.g., employee  degree (BS, MS, Ph.D.)).  Solution: make them into separate tables. 13

14.  http://en.wikipedia.org/wiki/Database_nor malization http://en.wikipedia.org/wiki/Database_nor malization  http://en.wikipedia.org/wiki/First_normal_ form http://en.wikipedia.org/wiki/First_normal_ form  http://en.wikipedia.org/wiki/Second_norm al_form http://en.wikipedia.org/wiki/Second_norm al_form  http://en.wikipedia.org/wiki/Boyce- Codd_normal_form http://en.wikipedia.org/wiki/Boyce- Codd_normal_form  http://en.wikipedia.org/wiki/Fourth_norma l_form http://en.wikipedia.org/wiki/Fourth_norma l_form 14

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