dbsystems chapter 3 data normalization get data properly tabled! based on g. post, dbms: designing...

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Chapter 3

Data Normalization

Get data properly tabled!

Based on G. Post, DBMS: Designing & Building Business

Applications

University of ManitobaAsper School of Business

3500 DBMSBob Travica

Updated 2015

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Normalization

The process of putting data into the format of relational databases or organizing data into

correctly designed tables.

Tables should be designed so that a) problems (anomalies) with insertion, deletion and

modification of data are avoidedb) redundancy is reducedc) data quality is preserved (completeness, consistency)

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Relational Database Terminology

Relational database: A collection of tables (relations). Tables store atomic data.

Table: A collection of columns (attributes, properties, fields)

describing an entity (class).

Table is also a collection of rows (records) each with the same number of columns.

Each row represent an object (an instance of a class).

EmployeeID TaxpayerID LastName FirstName HomePhone Address

12512 888-22-5552 Cartom Abdul (603) 323-9893 252 South Street15293 222-55-3737 Venetiaan Roland (804) 888-6667 937 Paramaribo Ln22343 293-87-4343 Johnson John (703) 222-9384 234 Main Street29387 837-36-2933 Stenheim Susan (410) 330-9837 8934 W. Maple

Attributes/Properties

Rows/Objects

Entity (Class): EmployeeTable: Employee

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Relational Database Terminology – Primary Key

Every table has a primary key (key) – an attribute that uniquely identifies each row (e.g., EmployeeID on previous slide)

Primary key can span more than one column combined (combined, composite, concatenated) key.

Note: Watch for data types (e.g., number vs. text) and naming rules (arbitrary but consistent).

OrderItem

OrderID ItemID Quantity 1 229 2 1 253 4 2 229 1 2 555 4

Primary key can be generated automatically by DBMS – surrogate key.

Other attributes are called non-key columns. A non-key depends on key.

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Relational Database Shorthand Notation

Customer(CustomerID, LastName, FirstName, Address, City, State,

ZipPostalCode, TelephoneNumber) *

Table nameNon-key columns

Primary key is underlined

• Note: Telephone number can be used as a “backup key.”

• Shorthand notation is good for analysis but not for official diagrams. Do not use it in your assignments and exams.

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Class Diagram to Schema

Customer

Order

Salesperson

Item

OrderItem

1

*

1

*

1

1*

*

Tables Diagram – Schema(Normalized)

Class Diagram (Non-Normalized)

Customer

Order

Salesperson

Item

1

*

1

*

*

*

OrderItem

Association class

(ItemOrdered,

OrderDetail, etc.) Another new detail: Foreign keys shown in a complete schema.

places serves

contains

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Customer(CustomerID, Name, Address, City, Phone)

Salesperson(EmployeeID, Name, DateHired)

Order(OrderID, OrderDate, CustomerID, EmployeeID)

OrderItem(OrderID, ItemID, Quantity)

Item(ItemID, Description, ListPrice)

Shorthand Notation for

Normalized Tables Diagram – Foreign Key

• Foreign Key (FK) = Attribute that is a (primary) key in another table (e.g., CustomerID in Order).

• Logic & naming of OrderItem: Replacing the Order-Item M:M relationship with two 1:M relationships. Also common name: OrderDetail.

• The OrderItem key is a combination of FKs (OrderID+ItemID).

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Video Store Transaction Processing System (VSTPS):Classes, Columns & Business Rules

Customer table Key: CustomerID Attributes:

Name Address Phone

Video table Key: VideoID Attributes :

Title RentalFee Rating…

RentalTransaction table Key: TransactionID Attributes :

CustomerID Date

VideoRented table Key: TransactionID + VideoID Attributes:

Copy#

Master Data (“Static”)—Market & Inventory Entities

(don’t change often)

Transaction Data (“Dynamic” )— Operations Entities(change more often)

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Business Rules and Class Diagram for VSTPS

Business Rules:

•A customer can have many rental transactions, each being for a specific customer.

•A transaction can include many video titles, and a title is in many transactions.

•A transaction can include just one copy of a video title.

Customer VideoTitle

RentalTransaction

1

* *

*has includes

?

VideoRented

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Schema for VSTPS

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Customer(CustomerID, LastName, FirstName, Address, City, …)

VideoRented(TransID, VideoID, Copy#)

Video(VideoID, Title, RentalFee)

RentalTransaction(TransID, RentDate, CustomerID)

Transaction data

You can draw a normalized schema based on knowledge of multiplicity and data analysis you already have!

1

1

1

*

*

*

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• How to get to those four tables using normalization logic? Why not simple design

for recording rentals:VideoRental

Poor design because:• Master data (Customer , Video) repeat for each transaction - high redundancy.

VideoRental(Rec#, CustomerID, LastName, FirstName,… VideoID, Title, RentalFee, Copy#, Date)

• Deletion of transaction data causes deletion of master data and reverse – deletion anomaly: Cannot delete target data but more (or less) than wanted.• A new customer can’t be added without adding a new video and reverse – insertion anomaly: Data can’t be added without corrupting other data.

• To change customer name, all records must be rewritten – update anomaly: Data can’t be updated only in a single master record.

• Conclusion: From the normalization perspective, data must be properly designed in order to avoid CRUD* anomalies and reduce redundancy.

Why Normalize – Avoiding Data Anomalies

Test:

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Normalization

A process of splitting a chunk of data to arrive at clear master and transactional classes. Each many-to-many relationship must be replaced by 2 one-to-many relationships.

Customer Video * rents *

RentalTransaction

1

* *

*has

includes

1.

Customer Video

RentalTransaction

1

**

*has contains

VideoRented (copy#)1 includes *

1 is rented

*

2.

How to track copies of a same video?

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Normalization Process

Interview users, understand output needed. Put data into a large table (RentalForm).

Pick out attributes. Find repeating groups

(sections).

Look for potential keys.

Identify computed values.

RentalForm(TransID, RentDate, (CustomerID, Name, Address, City, State, …),(VideoID, Copy#, Title, RentalFee))

Focus is on logic not really using such process in practice.

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Problems with Repeating Groups (Sections)

RentalForm(TransID, RentDate, (CustomerID, Phone, Name, Address, City, State, …),(VideoID, Copy#, Title, Rent))

TransID RentDate CustomerID LastName Phone Address VideoID Copy# Title Rent1 4/18/02 3 Washington 502-777-7575 95 Easy Street 1 2 2001: A Space Odyssey $1.501 4/18/02 3 Washington 502-777-7575 95 Easy Street 6 3 Clockwork Orange $1.502 4/30/02 7 Lasater 615-888-4474 67 S. Ray Drive 8 1 Hopscotch $1.502 4/30/02 7 Lasater 615-888-4474 67 S. Ray Drive 2 1 Apocalypse Now $2.002 4/30/02 7 Lasater 615-888-4474 67 S. Ray Drive 6 1 Clockwork Orange $1.50

Repeating Groups

• Repeating groups cause

- high redundancy

- update anomaly (must run through all records)

- insertion anomaly as errors in data (fake CustomerID if new video added)

- deletion anomaly (can’t delete simply what is needed)

• If there are repeating sections, the table is not in the first normal form (1NF).

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First Normal Form (1NF)

1NF: A table is in 1NF if it does not have repeating sections.

Normalization Procedure: Remove repeating sections by splitting the initial table into new tables. Preserve associations between the initial table and new tables by replicating

the initial key.

RentalTransaction(TransID, RentDate)

Video(TransID, VideoID, Copy#, Title, RentalFee)

Customer(TransID, CustomerID, Phone, Name, Address, City, State, ZipCod)

NewReminder of

initial table

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Problems with First Normal Form

There are problems in the relationship between the key and non-keys.

Concept of Functional Dependence: An attribute depends on another attribute if the change of its value is

caused by a change of the other attribute. The key column must be sufficient for determining values of the non-

key columns.

TransID VideoID Copy# Title RentalFee1 1 2 2001: A Space Odyssey $1.501 6 3 Clockwork Orange $1.502 8 1 Hopscotch $1.502 2 1 Apocalypse Now $2.002 6 1 Clockwork Orange $1.50

Video

Problems apply only to tables with combined keys! (A single-key table in

1NF is also in 2NF.)

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Problems with First Normal Form (cont.)

If any non-key column depends just on a part of the key there is partial functional dependence and the table is not in 2NF.

VideoID is sufficient for predicting titles and rental fees. Therefore,there is Partial Functional Dependence between the combined key and Title and RentalFee. **

Copy# depends on full key (TransID + VideoID) --Full Functional Dependency on the key. *


Combined determine

Sufficient to determine

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Second Normal Form (2NF)

2NF: A table is in 2NF if it is (a) is 1NF and (b) non-key columns depend on the entire key.

Normalization Procedure: Move TransID and Copy# into a new table VideoRented. Preserve the association between Video and VideoRented by

replicating VideoID in table VideoRented.


move movereplicate

VideoRented(TransID, VideoID, Copy#) New

Video(VideoID, Title, RentalFee) Resulting Video table *

X X

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Table Customer must also be brought into 2NF by moving TransID

into table RentalTransaction (already there) and replicating CustomerID

(see Slide 15).

Customer(TransID, CustomerID, Phone, Name, Address, City, State,…)


move replicate

Completed

Resulting Customer table


Finalize 2NF…

X

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Third Normal Form (3NF)

Problems with 3NF: If any non-key depends on some other non-key there is transitive dependence and the table is not in 3NF.

3 NF: Table is in 3NF if it is (a) in 2NF, and (b) each non-key attribute depends on the key only (or the key and nothing but the key).

Our design is already in 3NF! Check it below:


VideoRented(TransID, VideoID, Copy#)



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Table in 2NF: Sale(SaleID, CustomerID, SalespersonID,

SalespersonRank…)

3NF Example

• Solution – split table into 2 tables: :

Sale(SaleID, CustomerID, SalespersonID)

Salesperson(SalespersonID, SalespersonRank)

• Violation of 3NF: SalespersonRank (non-key) is dependent on SalespersonID, not SaleID.

• Forms beyond the 3rd are very rare and therefore reaching 3NF is sufficient for most of practical purposes.

•When we say “create schema”, we mean “create tables that are in 3NF”.

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Simplified Schema for VSTPS Using Different Key Design



RentalTransaction(TransID, CustomerID, VideoID, RentDate)

Note:

Video key can be made unique: VideoID = 85.1 (decimal place designates a copy),

or 85c1 (text type), or use a bar code for each video and copy (ItemID).

1

1

*

*

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Summary of Normal Forms (Must know by heart!)

1) If a table has repeating sections, there is huge redundancy, different classes are mixed together,

and all anomalies occur. Split the table, so that classes are clearly differentiated. Result: 1NF.

2) If a table has a combined key, non-key columns may depend on just a part of the primary key, and so there is partial functional dependency. Split the table so that in new tables non-keys depend on the entire key. Result: 2NF.

3) If a non-key depends on another non-key, there is transitive dependency. Split the table so that in new tables each non-key depends on the key and nothing but the key. Result: 3NF.

1NF: A table is in 1NF if it does not have repeating sections.

2NF: A table is in 2NF if it is in 1NF and non-key columns depend on the entire key.

3NF: A table is in 3NF if it is in 2NF and all non-key columns depend on the key only.

dbsystems chapter 3 data normalization get data properly tabled! based on g. post, dbms: designing...

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