Introduction to information systems T. Cornford, M. Shaikh is1 060 2013



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T. Cornford, M. Shaikh-13

Examiners do not expect 
any accompanying discs or files with the project work, and 
if you submit discs and files, they will not be looked at
. What 
Examiners do expect to receive, printed on paper, is a coherent account of 
the problem you tackled, the approach used and key details of how you 
analysed, designed and implemented your solution. Any accompanying 


Chapter 2: Preparing for the project work
21
printouts, screenshots, database tables, and so on are only intended to 
support the written report and should be carefully chosen and mentioned 
in the report. If you just rely on lots of ‘printouts’ and fail to write a 
coherent report, the Examiners cannot give you many marks. 
In the 
database project
, there are two central requirements – first, a 
carefully developed class diagram to show those aspects of the world that 
your databases will store data about. Second, a normalised data model 
that serves as the design that you will implement in software. The class 
diagram is the result of analysis work – you studying the world. The data 
model, which leads on from the class diagram, is the result of design work 
– taking the class diagram as its starting point. If the data model is well 
executed, with entities identified, relations clearly expressed and attributes 
specified, then the rest of the project – its implementation using the 
software – will follow smoothly. In preparing the data model students must 
show evidence that they have explicitly considered issues of normalisation. 
The details of class diagrams, data models and normalisation are topics 
covered in Chapter 8 of this subject guide.
For the 
spreadsheet
project
, it is less easy to identify a specific or 
linked set of fundamental requirements. To achieve a good mark, you need 
to select an appropriate problem to tackle – one that has a reasonable 
quantity of data and an underlying computational model that you can 
implement. The best projects draw on real data that relate to some area 
that you really understand or have researched. Weak projects are based 
on made-up data or examples from books that provide models that are too 
simple or too generic. Remember too, good spreadsheets are 

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