Home > Articles

This chapter is from the book

This chapter is from the book

Normalization is a process we can use to remove design flaws from a database. In normalization, we describe a number of normal forms, which are sets of rules describing what we should and should not do in our table structures. The normalization process consists of breaking tables into smaller tables that form a better design.

To follow the normalization process, we take our database design through the different forms in order. Generally, each form subsumes the one below it. For example, for a database schema to be in second normal form, it must also be in first normal form. For a schema to be in third normal form, it must be in second normal form and so on. At each stage, we add more rules that the schema must satisfy.

First Normal Form

The first normal form, sometimes called 1NF, states that each attribute or column value must be atomic. That is, each attribute must contain a single value, not a set of values or another database row.

Consider the table shown in Figure 3.4.

Figure 3.4Figure 3.4 This schema design is not in first normal form because it contains sets of values in the skill column.

This is an unnormalized version of the employee table we looked at earlier. As you can see, it has one extra column, called skill, which lists the skills of each employee.

Each value in this column contains a set of values—that is, rather than containing an atomic value such as Java, it contains a list of values such as C, Perl, Java. This violates the rules of first normal form.

To put this schema in first normal form, we need to turn the values in the skill column into atomic values. There are a couple of ways we can do this. The first, and perhaps most obvious, way is shown in Figure 3.5.

Figure 3.5Figure 3.5 All values are now atomic.

Here we have made one row per skill. This schema is now in first normal form.

Obviously, this arrangement is far from ideal because we have a great deal of redundancy—for each skill-employee combination, we store all the employee details.

A better solution, and the right way to put this data into first normal form, is shown in Figure 3.6.

Figure 3.6Figure 3.6 We solve the same problem the right way by creating a second table.

In this example, we have split the skills off to form a separate table that only links employee ids and individual skills. This gets rid of the redundancy problem.

You might ask how we would know to arrive at the second solution. There are two answers. One is experience. The second is that if we take the schema in Figure 3.5 and continue with the normalization process, we will end up with the schema in Figure 3.6. The benefit of experience allows us to look ahead and just go straight to this design, but it is perfectly valid to continue with the process.

Second Normal Form

After we have a schema in first normal form, we can move to the higher forms, which are slightly harder to understand.

A schema is said to be in second normal form (also called 2NF) if all attributes that are not part of the primary key are fully functionally dependent on the primary key, and the schema is already in first normal form. What does this mean? It means that each non-key attribute must be functionally dependent on all parts of the key. That is, if the primary key is made up of multiple columns, every other attribute in the table must be dependent on the combination of these columns.

Let's look at an example to try to make things clearer.

Look at Figure 3.5. This is the schema that has one line in the employee table per skill. This table is in first normal form, but it is not in second normal form. Why not?

What is the primary key for this table? We know that the primary key must uniquely identify a single row in a table. In this case, the only way we can do this is by using the combination of the employeeID and the skill. With the skills set up in this way, the employeeID is not enough to uniquely identify a row—for example, the employeeID 7513 identifies three rows. However, the combination of employeeID and skill will identify a single row, so we use these two together as our primary key. This gives us the following schema:

employee(employeeID, name, job, departmentID, skill)

We must next ask ourselves, "What are the functional dependencies here?" We have

employeeID, skill —> name, job, departmentID

but we also have

employeeID —> name, job, departmentID

In other words, we can determine the name, job, and departmentID from the employeeID alone. This means that these attributes are partially functionally dependent on the primary key, rather than fully functionally dependent on the primary key. That is, you can determine these attributes from a part of the primary key without needing the whole primary key. Hence, this schema is not in second normal form.

The next question is, "How can we put it into second normal form?"

We need to decompose the table into tables in which all the non-key attributes are fully functionally dependent on the key. It is fairly obvious that we can achieve this by breaking the table into two tables, to wit:

employee(employeeID, name, job, departmentID)

employeeSkills(employeeID, skill)

This is the schema that we had back in Figure 3.6.

As already discussed, this schema is in first normal form because the values are all atomic. It is also in second normal form because each non-key attribute is now functionally dependent on all parts of the keys.

Third Normal Form

You may sometimes hear the saying "Normalization is about the key, the whole key, and nothing but the key." Second normal form tells us that attributes must depend on the whole key. Third normal form tells us that attributes must depend on nothing but the key.

Formally, for a schema to be in third normal form (3NF), we must remove all transitive dependencies, and the schema must already be in second normal form. Okay, so what's a transitive dependency?

Look back at Figure 3.3. This has the following schema:

employeeDepartment(employeeID, name, job, departmentID, departmentName)

This schema contains the following functional dependencies:

employeeID —> name, job, departmentID, departmentName

departmentID —> departmentName

The primary key is employeeID, and all the attributes are fully functionally dependent on it—this is easy to see because there is only one attribute in the primary key!

However, we can see that we have

employeeID —> departmentName

employeeID —> departmentID

and

departmentID —> departmentName

Note also that the attribute departmentID is not a key.

This relationship means that the functional dependency employeeID —> departmentName is a transitive dependency. Effectively, it has a middle step (the departmentID —> departmentName dependency).

To get to third normal form, we need to remove this transitive dependency.

As with the previous normal forms, to convert to third normal form we decompose this table into multiple tables. Again, in this case, it is pretty obvious what we should do. We convert the schema to two tables, employee and department, like this:

employee(employeeID, name, job, departmentID)

department(departmentID, departmentName)

This brings us back to the schema for employee that we had in Figure 3.2 to begin with. It is in third normal form.

Another way of describing third normal form is to say that formally, if a schema is in third normal form, then for every functional dependency in every table, either

  • The left side of the functional dependency is a superkey (that is, a key that is not necessarily minimal).

or

  • The right side of the functional dependency is part of any key of that table.

The second part doesn't come up terribly often! In most cases, all the functional dependencies will be covered by the first rule.

Boyce-Codd Normal Form

The final normal form we will consider—briefly—is Boyce-Codd normal form, sometimes called BCNF. This is a variation on third normal form. We looked at two rules previously. For a relation to be in BCNF, it must be in third normal form and come under the first of the two rules. That is, all the functional dependencies must have a superkey on the left side.

This is most frequently the case without our having to take any extra steps, as in this example. If we have a dependency that breaks this rule, we must again decompose as we did to get into 1NF, 2NF, and 3NF.

Higher Normal Forms

There are higher normal forms (fourth, fifth, and so on), but these are more useful for academic pursuits than practical database design. 3NF (or BCNF) is sufficient to avoid the data redundancy problems you will encounter.

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.

Overview


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information


To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.

Surveys

Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.

Newsletters

If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information


Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.

Security


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.

Children


This site is not directed to children under the age of 13.

Marketing


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information


If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.

Choice/Opt-out


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information


Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents


California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure


Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020