1. M Taimoor Khan taimoorkhan@ciit-attock.edu.pk

2. Course Objectives 1) Basic Concepts 2) Tools 3) Database architecture and design 4) Flow of data (DFDs) 5) Mappings (ERDs) 6) Formulating queries (Relational algebra) 7) Implementing Schema 8) Built-in Functions 9) Extracting data 10) Working with Joins 11) Normalization 12) Improving performance 13) Advanced topics

3. Normalization Normalization! Functional Dependency Armstrong’s Axioms o First Normal Form (1NF) o Second Normal Form (2NF) o Third Normal Form (3NF) o Boyce - Codd Normal Form (BCNF)

4. Normalization  Normalization is the process of efficiently organizing data in a database  There are two goals of the normalization process: eliminating redundant data (for example, storing the same data in more than one table) and ensuring data dependencies make sense (only storing related data in a table)  Both of these are worthy goals as they reduce the amount of space a database consumes and ensure that data is logically stored

5. Anomalies  Insertion anomaly: We can not add a new record in courseRegistered unless the Course exists in the course table  Update anomaly: If we change the course description for IS380 from Database Concepts to Advance_Database_Concepts we have to make changes in more than one place or else the database will be inconsistent. In other words in some places the course description will be Advance_Database_Concepts and in any place were we forgot to make the changes the description still will be Database_Concepts.  Deletion anomaly: If student Russell is deleted from the database we also lose information that we had on his currentGPA and courses passed etc.

6. Functional dependency  A functional dependency occurs when one attribute in a relation uniquely determines another attribute. This can be written A -> B which would be the same as stating "B is functionally dependent upon A."

7. example  For Example there is a relation of student with following attributes. We will establish the functional dependency of different attributes: - STD (stId,stName,stAdr,courseName,credits)  stId stName,stAdr,courseName,credits  courseName credits  Now in this example if we know the stID we can tell the complete information about that student. Similarly if we know the courseName, we can tell the credit hours for any particular subject.

8.  EMP (eId,eName,eAdr,eDept,prId,prCost)  eId (eName,eAdr,eDept)  eId,prId prCost

9. Armstrong’s Axioms  Reflexivity rule: If A is a set of attributes, and B is a set of attributes that are completely contained in A, the A implies B  Augmentation rule: If A implies B, and C is a set of attributes, then if A implies B, then AC implies BC  Transitivity rule: If A implies B and B implies C, then A implies C  Union rule: If A implies B and A implies C, the A implies BC  Decomposition rule: If A implies BC then A implies B and A implies C  Pseudo-transitivity rule: If A implies B and CB implies D, then AC implies D

10. Normal Forms  Normalization is basically; a process of efficiently organizing data in a database  There are two goals of the normalization process: eliminate redundant data (for example, storing the same data in more than one table) and ensure data dependencies make sense (only storing related data in a table)  Both of these are worthy goals as they reduce the amount of space a database consumes and ensure that data is logically stored

11. First Normal Form  A relation is in first normal form if and only if every attribute is single valued for each tuple  This means that each attribute in each row, or each cell of the table, contains only one value.  Domain of the attribute is atomic and not multivalued Multi-valued attributes create problems in SELECT and JOIN operations

12. Example

13. Second Normal Form  A relation is in second normal form (2NF) if and only if it is in first normal form and all the nonkey attributes are fully functionally dependent on the key.

14. Example  This data is in first normal form

15.  But let’s pay attention to the City, State, and Zip fields: There are 3 rows of repeating data: one for Chicago, one for St. Paul and one for Regina. All have the same city, state and zip code

16.  The CustID determines all the data in the row, but U.S. Zip codes determines the City and State. (eg. A given Zip code can only belong to one city and state so storing Zip codes with a City and State is redundant)  This means that City and State are Functionally Dependent on the value in Zip code and not only the primary key.

17.  To be in 2NF, this repeating data must be in its own table.  So: Let’s create a Zip code table that maps Zip codes to their City and State.

18. Our Data in 2NF We see that we can actually save 2 rows in the Zip Code table by removing these redundancies: 9 customer records only need 7 Zip code records. Zip code becomes a foreign key in the customer table linked to the primary key in the Zip code table Customer Table Zip Code Table

19. Advantages of 2NF  Saves space in the database by reducing redundancies  If a customer calls, you can just ask them for their Zip code and you’ll know their city and state! (No more spelling mistakes)  If a City name changes, we only need to make one change to the database.

20. Normalization Normalization! Functional Dependency Armstrong’s Axioms First Normal Form (1NF) Second Normal Form (2NF) o Third Normal Form (3NF) o Boyce - Codd Normal Form (BCNF)

21. Lab Activity-13  Creating forms  Using form button  Create a split form  Create a multiple table form  Modify a form  Creating reports  Using report button

22. Next Lecture  Normalization continued…