VCE IT Theory Slideshows - ITA

By Mark KellyMcKinnon Secondary CollegeVceit.com

Updated by Jenny Gielb Chisholm Institute of TAFE, Dandenong

Database NormalisationVersion 1

Contents

• What is normalisation?• Why normalise?• Normal forms 1,2,3

What is normalisation?

• Organising the data in a relational database so…– Data repetition is minimised– Data access is maximised

Why normalise?• Removing data repetition saves lots of storage

space, speeds up data access and reduces errors.

• Changes need only be made in one place rather than in many places.

• More powerful data access is possible• Allows more information to be easily stored• Allows users to get all sorts of information out

of the stored data i.e. How many widgets did we sell last month?

The normal forms• Are called 1NF (first normal form) to 5NF, but

only 1-3 matter here.• Are guidelines (not laws) for structuring

database tables and fields.• Note: they are often applied instinctively as

part of skilled database design, and are not an extra step to do after databases are created.

REMEMBER – 1st and 2nd normal forms are stage/steps to achieving the objective, which

is 3rd normal form

History of Data Storage Techniques

• Data first stored as records only, everything on one line, usually on a tape – Sequential

• To get to a certain record you had to read through all the other records first, and start at the beginning each time. Took forever!

History of Data Storage Techniques

• Hard disks, and indexing, allowed businesses to store data more effectively.

• The data can then be stored in different areas on the hard disk and an index used to access it

Database Indexes• Indexes become very important• An index is a list that records where

everything is placed on the hard disks– The disk/platter– The track number– The section of track

Database Indexes• This meant that data could be stored anywhere on

hard disks, it didn’t have to all be together• The Index would find the required data no matter

what information you entered Also, computers were getting much faster, so accessing this data was much faster and easier so they could make

more complex indexes

• Have you ever looked up the index of a recipe book? You can look up Chocolate Sponge cake under Chocolate and Cakes

Database Indexes

Hierarchical databases

• The first types of databases

Hierarchical databases

• Data flowed from top to bottom. • To get the price of cucumber, you had to

know that it was Produce.• Slow, could only answer a few questions and

needed complex programs to use them• Could not answer the question ‘What aisle are

the lettuces in? Quicker to go find a shelf-packer.

Relational Databases

Then someone (Edgar F Codd?) invented a more complex indexing system that:•allowed access to all the data from any angle,•used codes to link tables together,•used ‘relationships’ to show the links between tables

Relational Databases

To answer the question – What aisle are Lebanese cucumbers in? The database uses the Item Type Code to look for the Contents Code to get the answer – Produce in Aisle 1

The Challenge• The challenge is to get data into these

meaningful, organised groupings• The data that you, as a programmer,

will be presented with, will be in a mess!

• If you are lucky important information will be in spread sheets, but it could be in files, hand written on scraps of paper, stuck on the side of the filing cabinet, even on the back of the office toilet door!

Steps1. Collect all the data2. Find out what information the users want from the

data3. Design the database4. Organise the data:

– Break it down into meaningful groups of data– Work out your linking codes so that each table points to

another one– Work out which data is being changed all the time and

which data is changed rarely

As you organise the data, you usually go through stages – these are called normalising the data.

The Normal Forms

• First Normal Form (1NF) – fields split up properly

• Second Normal Form (2NF) – first stage of breaking up the data into meaningful groupings called tables, some codes used

• Third Normal Form (3NF) – data completely broken up into tables and linked by codes

1NF 1NF

1NF• First Normal Form - sets the most basic rules

for an organised database• The 1NF guidelines are common sense.

1. Eliminate duplicate data where possible2. Break up fields so only one data item is in each

field3. Convert any data into correct format4. Start to organise the data into meaningful

groupings

Things 1NF wants

• No duplicate rows (records). Each row must be unique in some way.

• Each field entry can only contain one piece of data.– A name field containing “Fred Smith” has surname

and first name, violating 1NF.– A phone number field with more than one phone

number entered for a person

Things 1NF wants

Each field entry can only contain one piece of data. Why?•You cannot easily access the data embedded in the single field (e.g. grab a postcode)•You can’t use embedded data for sorting•You can’t use data like “2kg” as a number for calculations, sorting, summaries etc.

Your turn… repair this!

Customer ID Name Phone

111 Fred Smith 4566 3456

222 Mary Jones 4567 8900

333 Tim Blogs 3254 5676

Repaired!

Customer ID FirstName Surname

111 Fred Smith

222 Mary Jones

333 Tim Blogs

Now, customers can be sorted and searched by first name and/or surname separately.

Also, the names can be used individually, like “Dear Fred” instead of “Dear Fred Smith”

Repair This!Product ID Colour Weight

A345 Red 4kg

A568 Blue 300g

B695 White 1.5kg

Repaired!Product ID Colour Weight (g)

A345 Red 4000

A568 Blue 300

B695 White 1500

Repair This!

• An address like “3 Fred St, Sale, 3586” has 3 pieces of data: street address, town, postcode.

Customer ID Address

111 66 Lake Rd, Mentone, 3198

222 2/45 Richmond Lane, Richmond, 3121

333 135 Spring St, Melbourne, 3000

Repaired!

Now each field can be searched & sorted and used individually (e.g. addressing envelopes)

Customer ID Street Suburb Postcode

111 66 Lake Rd Mentone 3198

222 2/45 Richmond Lane Richmond 3121

333 135 Spring St Melbourne 3000

2NF 2NF

2NF – Second Normal Form• Achieving 2NF means 1NF has already been

achieved• Each normal form builds on the previous forms• Removes more duplicate data. • Deals with design problems that could threaten

data integrity.

2NF – Second Normal Form• Remove subsets of data that apply to multiple

rows of a table and place them in separate tables.

• Create relationships between these new tables and their predecessors using unique keys.

CUSTOMER

Customer ID Name Phone

111 Fred Smith 4566 3456

222 Mary Jones 4567 8900 (BH)3456 2314 (AH)

333 Tim Blogs 3254 56760402 697 495

Raw data

First normal form…

Repetition removed Fields broken up

but…

Customer ID Last Name First Name Phone1 Phone2

111 Smith Fred 4566 3456

222 Jones Mary 4567 8900 3456 2314

333 Blogs Tim 3254 5676 0402 697 495

Problems:•Trouble querying the table: “Which customer has phone # 3456 2314?” Have to search more than 1 field… messy.• Can’t enforce validation rules to prevent duplicate phone #s• Can’t enter three or more phone numbers• Waste of space for all people with only 1 number•If Mary Jones got married and changed her name, changes would need to be made in more than one record. If one change were missed, the integrity of the data would be damaged. •Making multiple changes like this is also time-consuming and repetitious, thereby eating up storage space.

Solution: Put the phone numbers into their own table as there can be more than one phone number for each name.

2nd Normal Form (2NF)CUSTOMER PHONE TABLE

Customer ID Phone

111 4566 3456

222 4567 8900

222 3456 2314

333 3254 5676

333 0402 697 495

Customer ID Last Name First Name111 Smith Fred222 Jones Mary333 Blogs Tim

Relationship

Called a ‘1 to many relationship’One customer record to many phone numbers

Also written as 1:many or 1:∞

Database Design

• The design would be drawn like this

Benefits:

•Name changes now only need to be made once.•Unlimited phone numbers for everyone!• No need to search multiple Phone fields• No need to search through all text to extract a particular phone number• All we need is a 1:many relationship between customer name table and customer phone table using the Customer ID as the key field.

2nd Normal Form (2NF)

Without 2NF: flat file With 2NF: relational

Department data is only stored once. So:• Less storage space required• Department changes now only made once, not once for each worker in that dept!

Another example

2NF

The table above is a problem. Let’s say {Model Full Name} is the primary key.The {Manufacturer Country} field is based on the {Manufacturer}

field, and will need to be constantly updated if manufacturers change their location.

To be properly 2NF, you’d need to do this…

Electric Toothbrush Models

Manufacturer Model Model Full Name Manufacturer CountryForte X-Prime Forte X-Prime ItalyForte Ultraclean Forte Ultraclean ItalyDent-o-Fresh EZBrush Dent-o-Fresh EZBrush USAKobayashi SR=60 Koboyashi ST-60 JapanHoch Toothmaster Hoch Toothmaster GermanyHoch X-Prime Hoch X-Prime Germany

2NFManufacturer Manufacturer Country

Forte Italy

Forte Italy

Dent-o-Fresh USA

Kobayashi Japan

Hoch Germany

Hoch Germany

Model ModelFullName

X-Prime Forte X-Prime

Ultraclean Forte Ultraclean

EZBrush Dent-o-Fresh EZBrush

ST-60 Koboyashi ST-60

Toothmaster Hoch Toothmaster

X-Prime Hoch X-Prime

Now the data is grouped – Manufacturer details in one table, Model details in the other, BUT how do you know which manufacturer makes which model now?

2NF

Make the same key fields in each table

Manufacturer Manufacturer CountryForte ItalyDent-o-Fresh USAKobayashi JapanHoch Germany

Manufacturer Model ModelFullName

Forte X-Prime Forte X-Prime

Forte Ultraclean Forte Ultraclean

Dent-o-Fresh EZBrush Dent-o-Fresh EZBrush

Kobayashi SR=60 Koboyashi ST-60

Hoch Toothmaster Hoch Toothmaster

Hoch X-Prime Hoch X-Prime

Set up the relationship

between the key fields in each table

3NF 3NF

3NFThird normal form (3NF) goes one step further•Use codes to minimize the amount of storage •Use codes as links to other tables so can find any information•Sets up relationships between tables•In each table only need to have fields that are dependant on the primary key•Also divides data as reference and transaction data.

Using the previous example - 2NFManufacturer Manufacturer Country

Forte Italy

Dent-o-Fresh USA

Kobayashi Japan

Hoch Germany

Manufacturer Model Model Full Name

Forte X-Prime Forte X-Prime

Forte Ultraclean Forte Ultraclean

Dent-o-Fresh EZBrush Dent-o-Fresh EZBrush

Kobayashi SR=60 Koboyashi ST-60

Hoch Toothmaster Hoch Toothmaster

Hoch X-Prime Hoch X-Prime

3NFTo get it to 3rd normal form, replace repeating data with codes.

MCode Manufacturer Manufacturer Country

1 Forte Italy

2 Dent-o-Fresh USA

3 Kobayashi Japan

4 Hoch Germany

MCode Model ModelFullName

1 X-Prime Forte X-Prime

1 Ultraclean Forte Ultraclean

2 EZBrush Dent-o-Fresh EZBrush

3 ST-60 Koboyashi ST-60

4 Toothmaster Hoch Toothmaster

4 X-Prime Hoch X-Prime

Reference and Transaction DataAll data can be classified as either reference data or transaction data

Reference Data is data that rarely changes and is ‘referred’ to (or used in lookups):•people’s names•addresses•Products

Starts with a unique code that is used in other tables

Reference and Transaction DataTransaction Data is data that is regularly changed (edit, add or delete) •when a customer buys something, •when someone withdraws money, •when someone wins a tournament.

Usually has a unique code, a date, and information about the transaction, i.e. the

purchase price and who made the purchase. Uses the codes set up in Reference Data tables

3NF

Field name underlining indicates key fields.You may have a gut feeling that this table is not good. But why?

3NF

Each attribute (‘field’) should be giving information about the key field (a particular tournament + year).

3NF

This is wrong because the DOB does not describe the key field (tournament). It describes a looked-up value (the tournament’s winner).

3NF FAIL

It’s like your mum keeping her knickers in your sock drawer because you’re related to her.

They don’t belong there!

Raw Data

1NF

First Name Last Name DOB Tournament Year

Chip Masterton 14/03/1977 Indiana Invitational 1999

Al Fredrickson 21/07/1975 Indiana Invitational 1998

Bob Albertson 28/09/1968 Cleveland Open 1999

Al Fredrickson 21/07/1975 Des Moines Masters 1999

• Data broken up into separate fields• Date of birth converted into proper format

2NF

• Data grouped but …• Data is still repeated

Player Code First Name Last Name DOB1 Chip Masterton 14/03/19772 Al Fredrickson 21/07/19753 Bob Albertson 28/09/1968

Player Phone Numbers

Tournament Winners

Player Code First Name Last Name Tournament Year1 Chip Masterton Indiana Invitational 19992 Al Fredrickson Indiana Invitational 19983 Bob Albertson Cleveland Open 19992 Al Fredrickson Des Moines Masters 1999

3NF

• Data grouped meaningfully - Tournaments, Players, Winners• No repeating data• Codes used to link tables• Relationships created

TournamentCode Tournament1 Indiana Invitational2 Cleveland Open3 Des Moines Masters

Player Code TournamentCode Year1 1 19992 1 19982 3 19993 2 1999

Player Code First Name Last Name DOB1 Chip Masterton 14/03/19772 Al Fredrickson 21/07/19753 Bob Albertson 28/09/1968

Tournaments

Players

Tournament Winners

Reference and Transaction Data

• Transaction Data– The Tournaments Winners tables is regularly

updated, every time someone wins a tournament

• Reference Data– The Players table only changes when someone

else joins or leaves a tournament– The Tournaments table changes when the

tournament name changes or new tournaments are added or deleted.

Reference DataTournamentCode Tournament

1 Indiana Invitational2 Cleveland Open3 Des Moines Masters

Player Code First Name Last Name DOB1 Chip Masterton 14/03/19772 Al Fredrickson 21/07/19753 Bob Albertson 28/09/1968

Player Code TournamentCode Year1 1 19992 1 19982 3 19993 2 1999

Transaction Data

• Unique code• Lookup data• Changed rarely

• Uses codes from reference data• Has extra information about event• Changes frequently

Tournaments

Players

Tournament Winners table

Entering the data

Don’t worry about the logistics of putting the codes into the data yet. This is dealt with later in the program.

Normalise this dataBounces Online Books

Name Address Book purchased Item Cost Date of purchase Quantity Total Cost

Tom Jones 56 Latrobe Street,Melbourne, VIC 3000 The Girl in the Hornet's Nest $24.95 08/03/2011 1 $24.95

Tom Jones 65 Latrobe Street,Melbourne, VIC 3000 Curiosity Killed the Cat $14.95 08/03/2011 1 $14.95

Mary Small 236 Smith Street, Collingwood VIC 3002 Lord of the Necklaces $18.95 10/03/2011 2 $37.90

Mary Small 237 Smith Street, Collingwood VIC 3002 The Girl in the Hornet's Nest $24.95 10/03/2011 1 $24.95

Fred Blogs 45 High Street, Sydney, NSW, 2000 The Hobby $13.95 12/03/2011 2 $27.90

Fred Blogs 45 High Street, Sydney, NSW, 2000 Lord of the Necklaces $24.95 12/03/2011 1 $24.95

Fred Blogs 45 High Street, Newcastle, NSW, 2000 The Girl in the Hornet's Nest $24.95 12/03/2011 1 $24.95

First stage - 1NFFirst Name

Last Name Address1

Address2 Suburb State Postcode Book purchased Item Cost

Date of purchase Quantity Total Cost

Tom Jones56 Latrobe Street Melbourne VIC 3000

The Girl in the Hornet's Nest $24.95 08/03/2011 1 $24.95

Tom Jones65 Latrobe Street Melbourne VIC 3000

Curiosity Killed the Cat $14.95 08/03/2011 1 $14.95

Mary Small236 Smith Street Collingwood VIC 3002Lord of the Necklaces $18.95 10/03/2011 2 $37.90

Mary Small236 Smith Street Collingwood VIC 3002

The Girl in the Hornet's Nest $24.95 10/03/2011 1 $24.95

Fred Blogs 45 High Street Sydney NSW 2000The Hobby $13.95 12/03/2011 2 $27.90

Fred Blogs 45 High Street Sydney NSW 2000Lord of the Necklaces $24.95 12/03/2011 1 $24.95

Fred Blogs 45 High Street Sydney NSW 2000The Girl in the Hornet's Nest $24.95 12/03/2011 1 $24.95

Second Stage – 2NFCustomerCode

First Name Last Name Address1 Address2 Suburb State Postcode

116 Tom Jones56 Latrobe Street Melbourne VIC 3000

457 Mary Small 236 Smith Street Collingwood VIC 3002

890 Fred Blogs 45 High Street Sydney NSW 2000

CustomerCode Book purchased Item CostDate of

purchase Quantity Total Cost

116The Girl in the Hornet's Nest $24.95 08/03/2011 1 $24.95

116 Curiosity Killed the Cat $14.95 08/03/2011 1 $14.95

457 Lord of the Necklaces $18.95 10/03/2011 2 $37.90

457The Girl in the Hornet's Nest $24.95 10/03/2011 1 $24.95

890 The Hobby $13.95 12/03/2011 2 $27.90

890 Lord of the Necklaces $24.95 12/03/2011 1 $24.95

890The Girl in the Hornet's Nest $24.95 12/03/2011 1 $24.95

Customer table

Books Purchased table

Third Stage - 3NFCustomer Table

CustomerCodeFirst Name Last Name Address1 Address2 Suburb State Postcode

116 Tom Jones 56 Latrobe Street Melbourne VIC 3000457 Mary Small 236 Smith Street Collingwood VIC 3002890 Fred Blogs 45 High Street Sydney NSW 2000

Purchases TableCustomerCode BookCode Date of purchase Quantity Total

116 1 08/03/2011 1 $24.95116 15 08/03/2011 1 $14.95457 36 10/03/2011 2 $37.90457 1 10/03/2011 1 $24.95890 4 12/03/2011 2 $27.95890 36 12/03/2011 1 $28.95890 1 12/03/2011 1 $24.95

Books TableBookCode Book Name Genre Item Cost

1 The Girl in the Hornet's Nest Murder Mystery $24.9515 Curiosity Killed the Cat Romance $14.9536 Lord of the Necklaces Fantasy $18.954 The Hobby Fantasy $13.95

Reference and Transaction Data

• Which tables are Reference Data tables?– Customer table– Book table

• Which table is a Transaction data table?– Purchases table

The front-end screen would look something like this:

Purchases data entered into the Transaction table, with drop-down lists which use data from the

Reference Data tables

In other words

• Let X → A be a nontrivial FD (i.e. one where X does not contain A) and let A be a non-key attribute. Also let Y be a key of R. Then Y → X. Therefore A is not transitively dependent on Y if and only if X → Y, that is, if and only if X is a superkey.

’kay?

By Mark KellyMcKinnon Secondary Collegevceit.com

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