A Case Study Using Data Analytics and Visualization

Running head: A CASE STUDY USING DATA ANALYTICS AND VISUALIZATION
A Case Study Using Data Analytics and Visualization
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A CASE STUDY USING DATA ANALYTICS AND VISUALIZATION1
Table of Contents
Introduction................................................................................................................................3
Main Body..................................................................................................................................4
Task 1 Summary of Variable, Ordered Quantity and Recommend...........................................4
Task 2.1 Correlation between the ordered quantity and other independent variables...............4
Task 2.2 Modelling in Order to Predict Order Quantity............................................................5
Initial Model to Estimate the Order quantity.........................................................................5
New Model to Estimate the Order Quantity..........................................................................7
Task 2.3 Effects of Introducing Interaction Variable.................................................................8
Task 3.1 Continuation of Predictive Modelling.........................................................................9
Task 3.2 Probability.................................................................................................................10
Task 3.3 Time Series Analysis.................................................................................................10
Conclusion................................................................................................................................10
Appendices...............................................................................................................................12
Task 1.......................................................................................................................................12
Table 1: Summary Statistics for Order Quantity and Recommended..................................12
Figure 1: Distribution of Order Quantity.............................................................................12
Figure 2: Distribution of Recommended..............................................................................13
Task 2.1....................................................................................................................................13
Table 2: Correlation Coefficient for the Variables with Order Quantity.............................13
Task 2.2a..................................................................................................................................14
Table 3: Initial Regression Model........................................................................................14

A CASE STUDY USING DATA ANALYTICS AND VISUALIZATION2
Task 2.2b..................................................................................................................................15
Table 4: Final Regression Model.........................................................................................15
Task 2.3....................................................................................................................................15
Table 5: Interaction Analysis...............................................................................................15
Task 3.1....................................................................................................................................16
Table 6: Likelihood of Recommending (a)..........................................................................16
Table 7: Accuracy of the model...........................................................................................16
Table 8: Overall Model Fit...................................................................................................16
Task 3.2....................................................................................................................................17
Table 9: Log-Likelihood and the Probability of Recommending MDCB...........................17
Task 3.3....................................................................................................................................17
Figure 3: Forecasting of the Pale Ale Production................................................................17

A CASE STUDY USING DATA ANALYTICS AND VISUALIZATION3
Introduction
Australia based micro-brewery company Mad Dog Craft Beer produce the Pale Ale
Beer majorly and mainly operates in Melbourne and the Victoria. It has experience of less
than years in the brewing ale. The company sales its product in two way, wither directly to
the consumers and indirectly through the sales representatives of pubs, restaurants, bottle
shops and the bars. Despite of its limited operations, this company is growing faster from the
last two years. The company has reported that it is going to increase the brewing capacity by
3 million liters per annum. They assume that they can meet the increasing demand of the pale
alee beer. Mad Dog Craft Beer, now, wants to shift in business climate within next 5 years.
So, before moving the business the management team of the company wants to investigate
and examine the relation with the customer base. Moreover the company wants a formal
procedure to forecast accurate demand and supply to adjust the production needs. Basically,
the management needs to do the analysis of the relation with the customer and wants to
forecast the demand and supply of the market to manage the production.
The analysis needs the data on the parameters, the loyalty of the customer, type,
region, rating of the company according to the customers and the level consumption of the
products produced by customers of the Mad Dog Craft Beer. BEAUTIFUL-DATA has
collected the data by conducting a large -scale survey focusing on the clients Mad Dog Craft
Beer. The collected data are added with the extra information stored in Mad Dog Craft Beer’s
data store. The survey collects the data on 200 observations on the three types of information.
The information is about the loyalty, distribution channel, customer’s perception about the
company and the ordered quantity and the relationship with company. The excel file contains
the data on the variables that are ordered quantity, quality, advertising, brand image, order
fulfillment, shipping speed and shipping cost.