1. Normalization By Albert Lin

2. 2 Basics Process of efficiently organizing data in a database. Goals Eliminate redundant data Ensure data dependency sensibility

3. 3 Benefits Faster sorting and index creation Larger clustered indexes Narrow and compact indexes Fewer indexes per table. Fewer null values Less inconsistencies

4. 4 Brief Description of Normal Forms 1 st Normal Form No repeating groups 2 nd Normal Form Each column depends entirely on the primary key. 3 rd Normal Form Each column depends directly on the primary key. 4 th Normal Form Isolate independent multiple relationships. 5 th Normal Form Isolate Semantically related multiple relationships. Boyce-Codd Normal Form Non Trivial dependencies between candidate keys. Optimal Normal Form Limited to simple Facts Domain-Key Normal Form No modification anomolies

5. 5 Additional Information 1 st Normal Form Addresses the structure of an isolated table. 2 nd, 3 rd and Boyce Codd Normal Form Addresses 1-1 and 1-many relationships. 4 th and 5 th Normal Form Many-Many relationships. These forms are cumulative.

6. 6 Anomalies Insertion Anomalies Duplication of data enforced impossible due to entity integrity Deletion Anomalies Leads to undesired loss of data. Modification Anomalies Modification of multiple rows can lead to inconsistencies. Databases that are sufficiently normalized can reduce anomalies from occurring.

7. 7 Tips Make a table for each list. Use non-meaningful primary keys Eliminate Repeating Groups Eliminate Columns not dependent on Primary Key Each table should have an identifier Should only store data for a single type of entity. Avoid null columns

8. 8 Additional Tips Records are free, new fields are expensive. Know when data requires duplication Use referential integrity The higher normal form generally results in faster data retrieval.

9. 9 Questions to ask What data do you need? What are you going to do with the data? How are the data related? What is the future of the data?

10. 10 Examples of Bad Databases SIDClassTimeLocationProf_ID 0015CS16610:30MH22634215 1205CS14612:00MH22525123 0025CS1661:30MH22234215 0015CS1518:00MH22224215 2531CS1569:00MH42225124 1205CS12010:30DH25112412 2522CS0468:00MH22434215 1523CS1405:00MH42225123 0015CS1403:00MH42234215

11. 11 Problems with the database In a large scale database, information would be repeated numerous times, resulting in redundant data Retrieval of data would be difficult and long Index creation would be difficult.

12. 12 In Practice Many databases are “de-normalized” to some degree. This is due to performance issues. It may require fewer joins and result in faster retrievals. However, before doing “de-normalization” performance issues must exist and de- normalization must dramatically improve it before introducing a suboptimal design A de-normalized table can be harder to update.

13. 13 Overall topics Normalization helps organization and speed of organizing a database, which can help a company produce a database system that is quick and easily accessible. The higher the normal form, the less chance anomalies will arise. In case of performance issues, de- normalization can be done in order to increase performance.

14. Final Motto: Strive for Single Themed Tables.

15. 15 References Litt, Steve. “Normalization”. 1996 http://www.troubleshooters.com/littstip/ltnorm.html “Rules of Data Normalization”. 2005. http://www.datamodel.org/NormalizationRules.html “Normalization” http://msdn.microsoft.com/library/default.asp?url=/library/en- us/createdb/cm_8_des_02_2oby.asp Chung,Luke. “Database Normalization Tips”. FMS. 2001. http://www.fmsinc.com/tpapers/genaccess/databasenorm.html Janert, Phillip. “Practical Database”. IEEE. 2004. http://www.devx.com/ibm/Article/20859 Reus, Bernhard. “Databases”. University of Sussex. 2004. http://www.informatics.sussex.ac.uk/users/bernhard/db2005/Slides /dbXIII.pdf Wyllys, R.E. “Steps in Normalization” University of Texas at Austin. 2003. http://www.gslis.utexas.edu/~wyllys/DMPAMaterials/normstep.html #Section%206.%20Anomalies%20and%20Normalization