Business Intelligence Application and Development Interview Study Approval Form

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Faculty of Computing, Engineering & Media (CEM)
Coursework Brief 2020/21
Module name:
Business Intelligence Application and Development
Module code:
IMAT5264
Title of the Assignment:
East Midlands Candy Assignment
This coursework item is:
Summative
This summative coursework will be marked anonymously
Yes
The intended Learning Outcomes (LOs) that are assessed by this coursework are:
LO1: Identify the required components of a BI system by systematic analysis of a perceived
problem area, appraisal of available techniques and tools, and the critical evaluation of
developed systems.
LO2: Conceptual understanding of a range of predictive analysis techniques, critically evaluating
current research and new insights.
LO3: Design appropriate BI systems using appropriate BI approaches.
This coursework is:
Individual
This coursework constitutes 100% to the overall module mark.
Date Set:
Thursday, 25th March 2021
Date & Time Due:
Wednesday, 26th May 2021, 12h00
Your marked coursework and feedback will be
available to you on:
If for any reason this is not forthcoming by the due date your
module leader will let you know why and when it can be
expected. The Associate Professor Student Experience
(CEMstudentexperience@dmu.ac.uk) should be informed of any
issues relating to the return of marked coursework and
feedback.
Note that you should normally receive feedback on your
coursework by no later than 20 University working days after
the formal hand-in date, provided that you have met the
submission deadline.
Wednesday, 23rd June 2021
When completed you are required to submit your summative coursework:
1. As a Word or PDF Document via Turnitin
If for any reason Turnitin is not working at the date/time of the submission deadline, please provide it as an
attachment to an email to the module leader by the specified deadline date/time and a subsequent Turnitin
submission can be completed as soon as the facility is available again to use.
If you need any support or advice on completing this coursework please visit the Student Matters tab
on the Faculty of Computing, Engineering and Media Blackboard page.
Late submission of coursework policy: Late submissions will be processed in accordance with
current University regulations which state:
“the time period during which a student may submit a piece of work late without authorisation and have the
work capped at 40% [50% at PG level] if passed is 14 calendar days. Work submitted unauthorised more than
14 calendar days after the original submission date will receive a mark of 0%. These regulations apply to a
student’s first attempt at coursework. Work submitted late without authorisation which constitutes reassessment
of a previously failed piece of coursework will always receive a mark of 0%.”
Academic Offences and Bad Academic Practices:
These include plagiarism, cheating, collusion, copying work and reuse of your own work, poor referencing or
the passing off of somebody else’s ideas as your own. If you are in any doubt about what constitutes an
academic offence or bad academic practice you must check with your tutor. Further information and details of
how DSU can support you, if needed, is available at:
http://www.dmu.ac.uk/dmu-students/the-student-gateway/academic-support-office/academic-offences.aspx and
http://www.dmu.ac.uk/dmu-students/the-student-gateway/academic-support-office/bad-academic-practice.aspx
Tasks to be undertaken: See below
Deliverables to be submitted for assessment: See below.
How the work will be marked: See Appendix 3
Module leader/tutor name:
Caroline Khene
Contact details:
caroline.khene@dmu.ac.uk
Case Study: East Midlands Candy
East Midlands Candy (EMC) is a small local confectionary manufacturer founded in Leicester, UK in
1850. Over the years, the organisation has evolved to produce a range of sweet products, including
chocolates, crisps and snacks, and a range of cakes supplied to sweet shops, vending machine
companies, hotels, and cinemas. There is also a retail section which is offered through a network of
branches found in towns, cities and in large suburbs throughout in the East Midlands.
A new Chief executive has recently been appointed following the retirement of the previous CEO. The
new senior management team is now keen to upgrade the organisations IT provision to become more
market focused and efficient. As part of this initiative the management is considering setting up a new
department of ‘Business Understanding’. The purpose of this department is to assist management to
understand customers better and to make justified decisions on operational management. This
department will undertake Business Intelligence related activities and in particular will be focused on
using techniques in forecasting, and linear programming in relation to the company’s activities.
Your task is to prepare a management report in which to illustrate to management how the techniques
of forecasting and optimisation (linear programming), and Business Intelligence could be useful to
the organisation. As management knows little of these techniques, you need to demonstrate how they
will work in practice. For this purpose, data has been supplied for you to carry out some of the
techniques.
Requirements and Instructions
1. The report should be broken down into three parts (Part 1 – 3). Your report should include your
workings and/or spreadsheets for the practical exercises and a reference list. We will have access
to your SAS BI work on the SAS server so you do not need to supply anything other than the
screen shots of your SAS BI work within your report.
2. It is expected that you will prepare and submit a comprehensive word-processed, structured,
logical, technical report in the correct format.
3. The report is to be electronically submitted through the Turnitin link on the IMAT5264
Blackboard shell by 12h00 noon, Wednesday 26th May 2021.
4. A typical report structure includes: Title page, contents, introduction, and main body of report,
conclusions, recommendations, and appendix (where appropriate).
• Note: The title page should contain: Module code and your p-number (name optional),
assignment title, deadline date, module tutor’s name. You should include your p-number
in the footer of every page along with page numbers (there should be no page number
displayed on the title page).
5. Total word count: 3000 (±10%)
6. As a guideline for report writing, please do the course on ‘Writing a Business Report’ that has
been placed in the IMAT5264 collection on LinkedIn (click here to access it).
7. The marking criteria are supplied Appendix 3.
If you have any questions, please direct these to Caroline Khene at caroline.khene@dmu.ac.uk
Part 1 Decision Making Techniques (50%)
1.1 Forecasting
a) As a consultant at East Midlands Candy, you are required to introduce and motivate for the
use of Forecasting techniques by:
i.
ii.
Providing an overview of how forecasting techniques could be useful.
Discussing the challenges and/or implications that East Midlands Candy could face in
the application of forecasting approaches/processes?
Discussing the four keys questions that management at East Midlands Candy should
consider when measuring the success of their forecasting techniques.
iii.
b) Use the following guidelines and instructions for the application of forecasting techniques:
i. Review the data supplied in Appendix 1.
ii.
Use this data to demonstrate how the different products (A, B & C) show different
characteristics with regard to forecasting (Hint: identify and describe the pattern
using a time series plot).
Identify the most appropriate forecasting technique for each of the three products
given and justify your choice.
Give forecasts for Year 4, for each product.
Critically evaluate your results highlighting whether you consider the forecasting
model to be good or not (Hint: consider forecast accuracy).
iii.
iv.
v.
(NB: Please use Microsoft Excel to support your calculations)
(10 + 15 = 25 Marks)
1.2 Linear Programming/Linear Optimisation
a) Provide an overview of how optimisation and linear programming (LP) could be useful in
supporting decision-making at East Midlands Candy.
b) Discuss how optimisation mathematical modelling could be used in the area of the
production/manufacturing of candy products (Hint: identify possible decision variables,
results variables, and uncontrollable variables/parameters)
c) Use the following guidelines and instructions for the application of linear programming
techniques.
i.
Review Problem Case 1 (Production) and Problem Case 2 (Staff Allocation) in
Appendix 2.
Formulate a Linear Programming model for:
ii.
1) Problem Case 1 (Production)
2) Problem Case 2 (Staff Allocation)
NB: There is no requirement to solve this problem or make calculations. A model is
only required, which includes decision variables, a result variable, objective, and
uncontrollable variable.
(5 + 5 + 15 = 25 Marks)
Part 2 Business Intelligence Systems (30%)
The owners of EMC have asked you to develop a Business Intelligence application for the Sales
department. The Sales Department is currently split into three groups, each of which has responsibility
for one customer area (retail, wholesale and grocery). The members of each team are to be provided
with an Information Delivery Portal (IDP) page. The information displayed is to be relevant to each
sales group i.e. it is to be filtered to display the customer group they have a responsibility for. All
users can be considered low level IT users.
In Section 1 of the IDP page a web report is to be displayed showing the sales history for each product
group (a tab page for each year) in table form. This table should show as a minimum the sales totals
for each product group for that sales group. You may choose to add additional measures. Be aware
that as the designer you need to find an appropriate balance of detail for the user.
In Section 2 of the IDP page, a web report is to be displayed in a graphical format. This should show
sales to all customers in a selected product group. Refer to the data sets provided to identify these
groups. The user should be prompted as to which product group and year they are interested in.
Remember they should only see sales for their customer group. The graph format is your choice (pie
chart, bar chart etc.).
In section 3 of the IDP page produce a dashboard showing total sales of each product group for the
current year which is 2003. Set the range based on:-
Above target being +10% on 2002 sales
On Target being between 90% and 110% of 2002 sales Below target being less than 90% of 2002
sales.
Again the choice of gauge is yours; remember to limit the data to that sales group’s customers. You
will need to manually calculate the value to enter for each range. There is no way for SAS to calculate
this requirement.
The data is already registered in metadata within the SAS BI suite, within the shared folder.
The files you will need include – Candy_Customer, Candy_Products, Candy_Sales_History,
Candy_Time_Periods and Candy_Sales_Summary.
You will need to create information maps, filters and prompts as necessary to complete the tasks.
To achieve a pass you will need to demonstrate an understanding of SAS techniques as we have
covered in labs. To achieve a distinction level pass you will need to demonstrate your ability to
produce an application tailored to non-technical user needs. Refer to the marking sheet for more detail
on the marking.
Include samples of your work in your report and an evaluation of your system, identifying any areas
where this system could be improved – for example highlight shortcomings in the software.
Part 3: Compliance (legal), Ethics, and Privacy Issues in Business Intelligence (10%)
Compile a brief overview of compliance, ethics, and privacy issues that may affect East Midlands
Candy and the proposed business intelligence systems. Support your overview with possible examples
that apply to EMC, and the nature of its business.
Report format and structure (10%)
There are 10% of the marks allocated for the correct report structure and clarity of the supporting
material, including layout, clarity, grammar, spelling, referencing and appropriate depth of coverage.
Submit your structured word processed report. Your report should include your workings and/or
spreadsheets for the practical exercises and a reference list. These could include hand written and
scanned LP formulations, excel spreadsheets and a list of references used.
Refer to the marking grid provided in Appendix 3 for more details.
Appendix 1
Sales figures for three (3) products
Sales of three (3) products have been selected for a trial of forecasting methods. Sales of the three
products (in 000s) are shown in the tables below
Product A: Chocolate bar
Year
Winter
Spring
Summer
Autumn
1
9.5
9.3
9.4
9.6
2
9.8
9.7
9.8
10.5
3
9.9
9.7
9.6
9.6
Product B: Children’s treats
Year
Winter
Spring
Summer
Autumn
1
14.2
31.8
33.0
6.8
2
15.4
34.8
36.2
7.4
3
14.8
38.2
41.4
7.6
Product C: Adult Mint bar
Year
Winter
Spring
Summer
Autumn
1
11.4
12.6
13.0
12.8
2
13.8
14.0
14.8
15.2
3
15.6
15.8
16.2
16.6
Appendix 2
Problem case 1: Production
EMC produces two types of popcorn (standard and deluxe). The supply of sugar is limited to 40,000
kg a week. The standard popcorn uses 300g of sugar whereas the deluxe version uses 400g of sugar
per kg.
EMC also has a commitment to supply 1,000 kg of the standard popcorn to a local cinema.
A final constraint on production is that EMC only has 48 litres of colouring. The standard
product requires 8 millilitres per kg and the deluxe product requires 15 millilitres per kilo.
EMC sells popcorn to its customers at a profit of 50p per kg of standard and 80p per kg of the deluxe.
Formulate a linear programming model to maximise profit from the production/sales of popcorn. Do
not attempt to solve the problem.
Problem case 2: Staff Allocation
The main factory at EMC operates 24 hours a day, with staff working 9-hour shifts. Not
all production lines operate 24 hours. Some only operate for 9 hours and others for 18
hours each day. The demand for staff during each 3-hour period of the day is given
below. Formulate a linear programming model to determine the minimum number of
staff required in each 24 hour period. Do not attempt to solve the problem.
Time Period
Number of Staff Required
9:00-12:00
32
12:00-15:00
24
15:00-18:00
20
18:00-21:00
28
21:00-24:00
12
0:00-3:00
4
3:00-6:00
2
6:00-9:00
10
Appendix 3
Marking Scheme
0-39 Fail
40-49- Fail
50-59 Pass
60-69 Pass Merit
70-79 Pass
Distinction
80 +
Distinction
Forecasting
Techniques
(15%)
No attempt
Or incorrect
approach
used
An attempt to
evaluate the
given
data.
Inappropriate
methodolo
gy used.
Possibly
some wholly
incorrect
techniques used
in
places
Appropriate evaluation
of time series
Appropriate
methodology Forecasts
produced
Some minor errors
Good evaluation
of time series
Good methodology
Forecasts produced
Possibly a minor error
Good evaluation
of time series Good
methodology
Correct
Forecasts produced
Excellent evaluation of
time series Excellent
methodology
Forecasts produced at
a professional level
Forecasting
Evaluation
(10%)
No attempt or
incorrect
An Attempt
made
but incorrect in
several places or
no application to
the case study.
Evaluation showing an
understanding of the
area of forecasting.
Some errors of
understanding or
minimal application to
the case study
Good evaluation
showing a good
understanding of the
area of forecasting.
Possibly a few errors of
understanding or
minimal application to
the case study
Good evaluation
Showing real insight
into the technique
applied to the case
study throughout
As before but at a
professional level.
Difficult to fault
Linear
programming
Techniques
(15%)
No attempt
Or incorrect
approach
used
An attempt to
evaluate the
given
problems.
Inappropriate
methodology
used
Possibly some
wholly incorrect
techniques used
in
places
Appropriate
methodology
Optimisation models
created produced
Some minor errors
Good methodology
Optimisation models
produced Possibly a
minor error
Good methodology
Correct LP models
produced. Very minor
error in formulation
Excellent
methodology LP
models produced
difficult to fault
Linear
Programming
Evaluation
(10%)
No attempt or
incorrect
An Attempt
made
but incorrect in
several places or
no application to
the case study.
Evaluation showing an
understanding of the
area of LP. Some
errors of
understanding or
minimal application to
the case study
Good evaluation
showing a good
understanding of the
area of LP. Possibly
a few errors of
understanding or
minimal application to
the case study
Good evaluation
Showing real insight
into the technique
applied to the case
study throughout
As before but at a
professional level.
Difficult to fault
Information
Maps and
Filters
(5%)
Not attempted
or
demonstrates
no
understanding
of the
information
maps purpose
Attempt made
to create
information
maps but
possibly no
filters or
ineffective
information
maps
Appropriate
Information maps or
Filters created
Appropriate
Information maps
created with sensible
filters but with minor
omissions
Excellent Information
maps with useful fully
functioning filters that
are appropriate.
Information maps
produced to a
professional level
Web reports
(5%)
Not
attempted or
wholly
inadequate
Attempted but
with major
flaws
Reports produced with
one possibly not
meeting the spec or
with obvious
deficiencies. This
could include overly
complex
Appropriate reports
produced but possibly
with minor problems
Excellent reports
meeting user
requirements at a very
high level
Reports produced to a
professional
level
demonstrating a
sound understanding
of user needs
Dashboards
(5%)
Not
attempted or
wholly
inadequate
Attempted but
with major
flaws
Dashboard produced
possibly not fully
meeting the spec or
with obvious
deficiencies
Appropriate
Dashboard produced
but with possible
minor problems.
Static targets
Excellent Dashboard
meeting user
requirements at a very
high level. Dynamic
targets
Dashboards produced
to a professional
level
demonstrating a
sound understanding
of user needs
Development of
IDP (5%)
Not
attempted
Attempted but
not correct
Completed but
requires more
attention to detail in
layout and headings
etc. May not
understand different
user group needs.
Completed but
possible minor issues
in appearance
Good attention to
detail in creating the
page
Excellent attention to
detail- extras added to
make it more user
friendly
Evaluation of
System (10%)
Not
attempted
Attempt made
but too
superficial or
shows no
understanding
of BI systems
A reasonable attempt
made to evaluate the
system and software.
One area is either
missing or superficial
A good attempt made
to evaluate the system
and software.
Evaluation of some
areas vague or brief
but most covered
adequately.
An excellent attempt
made to evaluate the
system and software
An excellent attempt
made to evaluate the
system and software.
Shows evidence of an
in depth understanding
of the issues
Compliance
(10%)
Not
Attempted
Attempt made
but many
compliance
issues omitted
Several compliance
issues identified but
not complete
Major issues identified
and key factors
highlighted in report
maybe not fully
applied to the case
study
Major compliance
issues identified and
applied to the case
study
As before but shows a
level of understanding
not usually expected
from students at this
level
Report
Format and
Referencing
(10%)
Very
Poorly
attempt
Poorly
written,
unstructure
d, no
illustration(
s), none or
entirely
inappropri
ate
referencin
g
Understandable,
little structure,
no contents list
and not spell
checked, no or
questionable
illustration(s),
adequate
coverage of
sources, lacking
sufficient detail
in referencing
Reasonably
written,
adequate
structure,
contents list or
spell checked,
some
illustration(s),
adequate
coverage of
sources, lacking
sufficient detail
in referencing
Well written,
good structure,
contents list and
spell checked,
appropriate
illustration(s),
Appendices
through
coverage of
sources with
sufficient detail
in referencing
Very well
written,
excellent
structure,
contents list and
spell checked,
informative
illustration(s)
with
comprehensive,
informative and
relevant
referencing

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