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Lecture 6

Database Design and Management

Peter Flett

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Recap – why?

Data:“ The raw facts or observations that

are considered to have little or no value until they have been processed and transformed into information”

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Data

1. A series of non-random symbols, numbers, values or words.

1. A series of facts obtained by observation or research.

2. A collection of non-random facts.

3. The record of an event or fact.

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Types of Data

FormattedFree textImagesAudioVideoModels‘Hard’ and ‘Soft’ data

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Information

1. Data that has been processed so that they are meaningful

2. Data that has been processed for a purpose

3. Data that has been interpreted and understood by the recipient

4. Information acts to reduce uncertainty (risk) about a situation or event

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Examples of information

A bank statementA sales forecastA telephone directoryManagement reportFinancial reportMIS’s, DSS’s, ES’s, and ERP systems

Beware of paralysis by analysis

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Capturing Data

Many sources

Can often be problematic

Open to interpretation • E.g. different types of research

methodology• Spin doctoring• Lying with statistics

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Inputting Data

Inputting of data is tedious.

Hardware can help

Scanning information (still requires a degree of data entry

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Creating Information Data Process:

A process used to convert data into information.Examples include sorting, searching, filtering, summarising, classifying, calculating and combining

Data

TransformationProcess (the data process)

Information

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Knowledge

“An accumulation of information, building on existing ideas and experience”

This should be the result of information

Q. How does an organization retain knowledge?

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Relating data, information and knowledge

Data

Information

UnderstandInterpretDecide

Act upon

Decisions/Actions

Outcomes

LearnInterpret

Enhanced/Increased Knowledge

Converts

A cyclical improvement process?

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Perspectives on Information

Informative• Type of information & what it tells us

Nature of form• How is the information presented

Time interval• When is the information communicated to

us

Scope• The part of the org to which the info relates

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Value of Information

Tangible value• A value or benefit that can be measured

directly, usually in monetary terms• Value of information minus cost of

gathering information

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Value of Information

Intangible value• A value or benefit that is difficult or

impossible to quantify• E.g. Improvement in decision behaviour

minus cost of gathering information

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Sources of Information

Formal communication• reports, accounting statement,

programs, memos etc.

Informal communication• Conversation, notes etc.

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Information Quality

Time Content Form

Additional Characteristi

cs

Timeliness Accuracy Clarity Confidence in source

Currency Relevance Detail Reliability

Frequency Completeness

Order Appropriate

Time Period Conciseness Presentation Received by correct person

Scope Media Sent by correct channelsO’Brien (1993)

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Summary

Information can be derived from data in many different ways

Gathering and processing data costs money

Organizations use a wide variety of information for different purposes

The characteristics of that information have a major impact on organizational effectiveness

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The Design Process

Crucial, good design prevents,Redundant dataInconsistent dataInflexibility of useLimited sharing of dataLimited security

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Deletion - if student 12347 withdrew from course we would loose BUS fee information

Redundancy -course feerepeated

Insertion - A new course cannot be added until a student registers

Updating - If MBA fee changed we would have to alter records of all MSCstudents

For example

Student Reg No

Course

Fee

12345 ISM 400012346 MBA 350012347 BUS 420012348 ISM 400012349 MBA 3500

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5 steps to database design( Dowling)

1. What is the purpose of the database?

SMART: Specfic, Measurable, Achievable, Relevant, Time related

2. Determine the information requirements of the database

( these stages are all key parts of the system analysis that has to take place prior to implementation )

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5 steps to database design( Dowling)

3. Produce a logical model of the information requirements (E-R model) SSADM

4. Convert the logical data model to a physical data model

I.e. go from the conceptual world to the real worldFrom the E-R model to the Relational Model (normalisation)

5. Implement the physical design