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Class Agenda (04/09 through 04/16)

Review HW #8

Present normalization process

Enhance conceptual knowledge of database design.

Improve practical skills of database design.

Approach

Review goals of database design.

Identify and define vocabulary for normalization. Do an “intuitive” database design for a refresher. Discuss the characteristics of the three normal forms and

the characteristics of a data model in third normal form. Use the normalization process to do the same database

design. Compare results. Do more database design exercises using normalization

process.

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Review of database design goals

Protect the integrity of the data. Reduce data redundancy. Prevent data anomalies.

Provide for change. Prevent inflexible data structures. Anticipate changes.

Provide access to complete data for decision making.

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What is normalization?

Normalization is a formal, process-oriented approach to data modeling.

Normalization is the process of:

examining groups of data attributes; splitting them into appropriate entities; identifying the relationships between

the entities; and identifying appropriate primary and

foreign keys.

Same old/same old

Normalization should sound like what you have already done during database design.

The ultimate goals of design have not changed; we are just going to go about it in a slightly different way.

Let’s start with an application and doing it through “intuitive” database design. Student information grade screen design exercise

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Database Normalization

What will you know about database normalization? Define normalization. Know the vocabulary of normalization. Understand the process of normalization. Better understand the characteristics of an effective

database design.

What will you be able to do? Be able to identify the characteristics of each normal

form. Be able to tell whether or not a data model is in third

normal form. Potentially be able to use normalization to assist you

in the design of a database.

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Normalization process

Some refer to this as the “bottom-up” form of database design.

Contrast with the more intuitive “top-down” approach we have been using.

The results from the normalization process are stable, flexible entities. The results from the intuitive approach should be the same.

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Two methods of applying normalization

1. Use it to help in designing a database. Normalization starts with a single entity. Normalization breaks that entity into a series of

additional entities. More entities are discovered and named during the

process. Entities are linked during the process.

2. Use it to validate the design of a database. Identify entities from the meaning of the data. Create conceptual and logical data models. Apply the rules of normalization to ensure a stable,

non-redundant design.

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Vocabulary for normalization

A “functional dependency" is a relationship between attributes in which one attribute or group of attributes determines the value of another.

A “determinant” is an attribute or group of attributes that, once known, can determine the value of another attribute.

Examples of functional dependencies and determinants

A social security number determines your name and address. SSN name, address.

A vehicle id number determines the make and model of a car. VIN make, model.

Name and address are “functionally dependent” on SSN.

SSN “determines” name and address.

Functional dependency diagram format: CourseID CourseName, CourseDescription, CourseCredits ZipCode City, State PatientID, TreatmentDateTime TestResults

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Normalization process

Normalization is accomplished in stages. A “normal form” is a state (level of completeness) of a data model.

Unnormalized data: A data model that has not been normalized. It contains repeating groups and is not a stable model.

Unnormalized data is essentially one entity. The system under analysis is categorized as a single entity.

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Steps/forms/phases in Normalization

First normal form: Remove repeating groups.

Second normal form: Remove partial functional dependencies.

Third normal form: Remove transitive dependences

• Semester

• Year

• Student Name

• Student Address

• Student City

• Student State

• Student Zip Code

• Student ID

• Student College

• Student Major

• Student Minor

• Student Year

• Course ID

• Course Title

• Course Instructor

• Course Credits

• Grade

What attributes might be needed that aren’t visible

on the grade report?

Group all attributes in one “big” entity.

Identify a primary key for the entity.

Maybe studentID for this one.

Unnormalized data for grade report exercise

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First Normal Form

First normal form: Remove repeating groups. A repeating group is an attribute or group of attributes

that can have more than one value for an instance of an entity. If it is a single attribute, we have been calling it a “multi-valued” attribute.

To get a data model into first normal form: Identify repeating groups and place them as separate

entities in the model. Identify a primary key for the repeating group. The

key may be concatenated. Create the relationships between entities. Divide m:n relationships with appropriate intersection

entities.

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Second Normal Form

Second normal form: Remove partial functional dependencies.

A partial functional dependency is a situation in which one or more non-key attributes are functionally dependent on part, but not all, of the primary key. Partial functional dependencies occur only with

concatenated keys.

Examples of partial functional dependencies: PatientID, TreatmentDateTime PatName, TstResults,

TrtID, LocID CourseID, StudentID CourseTitle, Grade

Which entities developed during the transition to first normal form for the grade report have concatenated keys?

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Third normal form

Third normal form: Remove transitive dependencies. A transitive dependency occurs when a non-key attribute is

functionally dependent on one or more non-key attributes.

Third normal form examines entities with single primary keys and removes the “floating” or transitive dependencies.

It may be possible to have attributes that are determined by other attributes, rather than by the primary key. They must be removed into entities with appropriate primary keys.

Example of partial functional dependency: PatID, TrtDateTime TstResults, TrtType, TrtDescription,

LocName, TrtID, LocID

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Summary of normalization process

Examine and evaluate the logical data model for effectiveness. Find the repeating groups and put the model

into first normal form. Identify primary key fields for any new entities. Relate entities with foreign keys.

Find the functional dependencies. Identify the partial functional dependencies and put the model into second normal form. Identify primary key fields for any new entities. Relate entities with foreign keys.

Find the transitive dependencies and put the model into third normal form. Identify primary key fields for any new entities. Relate entities with foreign keys.

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Goal of normalization

A set of entities where each attribute in each

entity is dependent on the primary key, the whole

primary key, and nothing but the primary key.