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Business Case The CIO of Valeur, a large national supermarket/retail store chain has recently introduced a loyalty card program and keen to gain a more comprehensive understanding of the organisation’

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Business Case
The CIO of Valeur, a large national supermarket/retail store chain has recently introduced a loyalty card
program and keen to gain a more comprehensive understanding of the organisation’s clientele through
traditional transactional data as well as the newer and effective demographics analysis techniques. A close
friend, the CEO of Vigour has highly recommended you as an accomplished business analyst/consultant
for data warehousing and OLAP projects based on the outstanding work completed on the dimensional
modelling and design ph...

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Question Preview:

Business Case
The CIO of Valeur, a large national supermarket/retail store chain has recently introduced a loyalty card
program and keen to gain a more comprehensive understanding of the organisation’s clientele through
traditional transactional data as well as the newer and effective demographics analysis techniques. A close
friend, the CEO of Vigour has highly recommended you as an accomplished business analyst/consultant
for data warehousing and OLAP projects based on the outstanding work completed on the dimensional
modelling and design phase of a data warehouse at Vigour.
The CIO of Valeur, impressed by the commendation, has approached you with his interests in customer
analytics. The customer relationship management (CRM) team working under his supervision have already
put together a summarised data warehouse containing some transaction data and customer
demographics. Although the data is accurate and complete, the CIO believes the structure is not. He feels
there’s more information that can be captured by the warehouse. He’s very impressed with the power of
demographics as it is directly applicable to his client base.
He has two main business problems in mind. Firstly, improving the current dimensional model/
warehouse to capture all relevant information that applies to customers, such as demographics.
Secondly, using current data in the warehouse to better understand the customer base by identifying
customer behaviours and thereby potential sales and marketing opportunities. You have agreed to take
on this responsibility and deliver a complete report documenting your recommendations to improve the
dimensional model and your findings from the current warehouse.
What you are required to do
1. Suggest improvements to the dimensional model
Study the given dimensional model to determine what’s lacking in response to the business need. Identify
potential improvements to the dimensional model. This can be in the form of new attributes, new
dimensions, new measures or the use of dimension design techniques. Present your recommendations
with supporting evidence and the new dimensional model.
3. Create cubes and OLAP queries
The data warehouse (ValeurDW) is accessible from the Azure server (BUS5WB-SQLSVR02). Use SSDT to
create a multidimensional analysis project. Design and run OLAP queries to determine customer insights
(demographics, buying behaviours, sentiment and the combination of these). You may decide the number
of queries to run and you are free to use any query interface - MS Excel, SQL reporting, MDX or even the
Cube browser. 
Master of Business Analytics BUS5WB
La Trobe Business School
2
4. Recommendations
Make recommendations based on your findings, taking into account the natural progression of a typical
customer from low-value to high-value and the potential opportunities exposed in the consumer
dynamics. Recommendations can be simple as cross-sell, up-sell and down-sell or a notch-up sophisticated.
Deliverables
A report on the above activities undertaken for Valeur. The report should be compiled as a series of topics
of the abovementioned ‘to do’ list.
• The report should be compiled in Microsoft Word only, font size 11.
• It should not exceed 12 pages. Diagrams, tables and any other visualisation has to be in the main body
of the report.
• It should contain a reference to your SSAS project (project name) on the server and any other files.
• Make realistic assumptions on any information (schema or business requirements) that may be
missing in the above description. Mention all assumptions in the report.
Dimensional Model

DimTransactionDate
TransactionDateKey
TransactionDate
Day
Month
Quarter
Year
DimCustomer
CustomerKey
CustomerID
Age
Gender
Education
SuburbProfile
CreditRanking
DimProductCategory
ProductCategoryKey
ProductCategoryID
CategoryName
DimFeedback
FeedbackKey
FeedbackID
FeedbackService
FeedbackPrice
FeedbackVariety
FeedbackValue
FactTransactionSummary
CustomerKey
ProductCategoryKey
FeedbackKey
TransactionDateKey
TotalQuantity
TotalSale
Master of Business Analytics BUS5WB
La Trobe Business School
3
Rubric
Criteria Pass Credit Distinction High Distinction
Improve the
dimensional model
5 marks
A minimal
attempt at
improving the
dimensional
model.
A basic attempt at
improving the
dimensional model.
A complete
attempt at
improving the
dimensional model.
A complete
attempt at
improving the
dimensional
model with
precision focus on
integrating
transaction data,
and all aspects of
demographics.
Create cubes and
run OLAP queries
10 marks
A minimal
multidimensio
nal analysis
project with
minimal
reports,
findings, and
outcomes.
A basic
multidimensional
analysis project
with a decent
number of reports,
findings, and
outcomes.
A complete
multidimensional
analysis project
with a good
number of reports,
findings, and
outcomes.
A complete
multidimensional
analysis project
with an optimal
number of
reports, findings,
and outcomes
providing a broad
coverage.
Recommendations
for new markets
15 marks
A rudimentary
effort, limited
to a minimal
number.
A decent effort,
with some
actionable
recommendations.
A good effort, with
many actionable
recommendations.
A comprehensive
effort, covering all
actionable
recommendations 

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