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BUSINESS ANALYTICS

BUSINESS ANALYTICS
The Dude, a division of Lebowski industries, is a chain of big and tall men’s apparel stores operating throughout the country. The chainrecently ran a promotion in which discount coupons were sent to customers of other Lebowski stores. Data collected for a sample of 100 Lebowski credit card transactions at The Dude during a single day while the promotion was running are contained in the file name “DUDE”.

The DudeCard method of payment refers to charges made using a proprietary card (like a Macy’s or Nordstrom card). Customers who made a purchase using a discount coupon sent in the mail to them are referred to as “coupon” customers. All others are called “no coupon” customers.

Because the promotional coupons were not sent to regular Dude customers, management considers sales made to people presenting the promotional coupons as sales it would not otherwise make. Of course, The Dude also hopes that the promotional customers will continue to shop at its stores.
In addition, the following variables might need some clarification.

• “Items” refers to the total number of items purchased, i.e. the total number of SKUs scanned.

• “Net Sales” refers to the total dollar amount charged to the credit card.

Management at The Dude would like to use this sample data to learn about its customer base and to evaluate the promotion involving discount coupons.

They have asked you, the hotshot Business Analyst, to develop a managerial report. This report should contain the following information at a minimum.

1. An executive summary of your findings. This should be no more than 1 page double-spaced. The executive summary should answer the top three most important questions. And it is YOUR responsibility to tell management why those are the most important and why. Hint: Two of the most important variables will be Gender and Marital Status. But they are not the ONLY ones.

2. Percent frequency distribution for the key variables.

3. A column chart or pie chart showing the number of customer purchases attributable to each method of payment.

4. A cross-tabulation of type of customer (regular or promotional) versus net sales. Comment on any similarities or differences you see.

5. A scatter diagram to explore the relationship between net sales and customer age.

The final product will have a 1 page executive summary along with accompanying graphs/charts as appendices. Then, you can refer to the appendices when making a point about your data.

Hint: you may want to use the Pivot Table function in Excel to do this assignment. If you do, the data will fall into place for you.

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Business Analytics

Business Analytics
Order Description
A multinational organisation is about to embark on a project to implement a data warehousing solution alongside the formation of a business analytics department at its corporate headquarters.
In your role as a Business Data & Analytics Consultant you have been employed by the organisation to advise them on the processes and potential for the planned implementation.
You will prepare a maximum 4,000 word report for the organisation on the following areas:
1. Outline what data & information will be available to the organisation. This will need to include a summary of the organisation in geographical, operational and product/service terms.
2. Summarise from the literature what is meant by ‘data warehousing’ and how it can be used in conjunction with the data & information identified in section 1 above.
3. Provide an overview of the issues and processes involved in the implementation and adoption of the data warehouse.
4. Illustrate how three separate advanced business analytics techniques (for example; optimisation, probability distributions, regression etc) can be employed by the business analytics department, to inform organisational decision making, once the data warehouse is fully operational. Students can use actual data if available or simulated data to illustrate the separate techniques.
Further details:
It is expected that the report will contain charts, graphs, tables etc. as appropriate.
Assessment II – Key Points
1. Choose an organisation that makes the task easy / interesting / perhaps relevant to other studies and / or future career path.
– Who the organization is
– Where are they based
– Headquarters and regional pops
– How many shops
– How they distribute to customers
– What are their operations and their touch points

2. Don’t get too technical. This is not a computer science degree. No need to go into detail about architecture etc. (Kimball’s work goes too deep) other than the structure of a data warehouse.

3. Implementation is from an organisational behaviour perspective (e.g. Wixom & Watson 2001) rather than a technical perspective. How to implement data warehousing to support strategic and tactical decision making

4. 4,000 words is an absolute max. It may be far more than you need. Charts and diagrams are good!

5. The analytics methods to use on actual or, more likely, simulated data are three from data modelling, optimisation, probability distributions, data mining, regression and forecasting. correlation, weighted moving average, exponential smooth, visualizing data, SPSS.
6. Google Scholar is very useful for finding key academic papers, citation trails etc. Number of citations indicates the importance of the research. We expect you to draw upon academic research (journals etc.) to inform parts 2 and 3. Again, don’t go too deep and don’t go off on tangents etc. A paper’s abstract is a good indicator of whether it will be useful or not. Some journal articles may have free pdf / html links; others will need to be sourced through.

Responses are currently closed, but you can trackback from your own site.

Comments are closed.

Business Analytics

Business Analytics
Order Description
A multinational organisation is about to embark on a project to implement a data warehousing solution alongside the formation of a business analytics department at its corporate headquarters.
In your role as a Business Data & Analytics Consultant you have been employed by the organisation to advise them on the processes and potential for the planned implementation.
You will prepare a maximum 4,000 word report for the organisation on the following areas:
1. Outline what data & information will be available to the organisation. This will need to include a summary of the organisation in geographical, operational and product/service terms.
2. Summarise from the literature what is meant by ‘data warehousing’ and how it can be used in conjunction with the data & information identified in section 1 above.
3. Provide an overview of the issues and processes involved in the implementation and adoption of the data warehouse.
4. Illustrate how three separate advanced business analytics techniques (for example; optimisation, probability distributions, regression etc) can be employed by the business analytics department, to inform organisational decision making, once the data warehouse is fully operational. Students can use actual data if available or simulated data to illustrate the separate techniques.
Further details:
It is expected that the report will contain charts, graphs, tables etc. as appropriate.
Assessment II – Key Points
1. Choose an organisation that makes the task easy / interesting / perhaps relevant to other studies and / or future career path.
– Who the organization is
– Where are they based
– Headquarters and regional pops
– How many shops
– How they distribute to customers
– What are their operations and their touch points

2. Don’t get too technical. This is not a computer science degree. No need to go into detail about architecture etc. (Kimball’s work goes too deep) other than the structure of a data warehouse.

3. Implementation is from an organisational behaviour perspective (e.g. Wixom & Watson 2001) rather than a technical perspective. How to implement data warehousing to support strategic and tactical decision making

4. 4,000 words is an absolute max. It may be far more than you need. Charts and diagrams are good!

5. The analytics methods to use on actual or, more likely, simulated data are three from data modelling, optimisation, probability distributions, data mining, regression and forecasting. correlation, weighted moving average, exponential smooth, visualizing data, SPSS.
6. Google Scholar is very useful for finding key academic papers, citation trails etc. Number of citations indicates the importance of the research. We expect you to draw upon academic research (journals etc.) to inform parts 2 and 3. Again, don’t go too deep and don’t go off on tangents etc. A paper’s abstract is a good indicator of whether it will be useful or not. Some journal articles may have free pdf / html links; others will need to be sourced through.

Responses are currently closed, but you can trackback from your own site.

Comments are closed.

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