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Lecture 10

Rounding Up

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Denormalisation (controlled redundancy)

Trade offProvides quicker updatesAt the expense of retrieval

E.g have the results of calculations in tables rather than creating a query to create the result

Using the COURSE_TUTOR table instead of normalising it further

Further reading - Denormalisation - An `Optimal Database Design' Tactic (1993) Bernard W Bennetto and

Matthew C O Todd http://home.clara.net/tt-ltd/normalsn.html (abstract supplied)

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Denormalisation (controlled redundancy) Less computing resource needed

May suit the client

Can complicate the insertion and alteration of data

Three common examples1. Holding calculated value in parent table2. Holding calculated values in the same table3. Merging tables (see Dowling p65 for more detail)

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Multiple users

Single file – ok for single user

Typically database multi-user

front-end/back-end application

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An application consisting of two database files. The "back-end" database file contains the tables.

The "front-end" database file contains all other database objects (queries, forms, reports, macros, and modules) and links to the tables in the back-end database.

In Access need to convert database into MDE file

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Typically the back-end database is located on a network server, and copies of the front-end database are installed on individual users' computers.

Allows alteration to the front-end code without effecting the data

A file-server application not a client-server application

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Data Design

PurposeUse the right data type for data

elements E.g. time/date, text, numbers etc.

What operations are going to be carried out on the data?

8(see handout)

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Data types

Mathematical operations?What will the number represent

a measurement a percentage

Conversion Is a conversion rate going to change

over time Format of data may also need

converted

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Data types

Time – two different forms Dates Durations

Numeric data Represent a value e.g bank balance A string of digits e.g Student

registration number

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Data Types

Text values Access limits to 255 Can use memo – but cannot index this

data typeTime represented by Date/Time

As with other data types includes ‘masks’ to assist data input

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Data Types

Logical values True or False Yes No

Not just two values also ‘Null’ Avoid by having a default value (‘British’

in Workshop) Disallow if necessary

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Data Types

‘Null’ Unknown Unspecified Not applicable Currently unknown Was specified but is no longer needed

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Data Types

‘Null’ Can’t assume all nulls are the sameNull + PriceOfEggs = NullNull is a ‘token’ that represents a

missing valueUse encoding schemes if necessary

ISO standard for gender0=Unknown, 1=Male, 2=Female, 3= Not

applicable

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Data encoding schemesConventions and Standards should be,

Complete Unambiguous Not error prone Expandable Consistent Convenient Verifiable Well documented

Encoding schemes aim to provide consistency through repetition which in theory should lead to less errors

Y2K issues due to historic encoding schemes