MIS771 Descriptive Analytics and Visualisation

Published : 20-Oct,2021 | Views : 10

Question:

Describe the Audience for your Data Visualisation Describe the audience of the Data Visualisation you intend to create. This section should include a general description of the persona, questions they want to be answered, actions/outcomes your dashboard will be supporting, and the feeling you would like to convey.

Describe at a high level what types of charts you might use to display the data.Based on the data types you described earlier in this section, along with the objectives of the persona you described, describe what charts and visualisations do you think might work well to communicate the information.
Describe any data ethics considerations there with the data you intend to use.Describe any considerations you think you should keep in mind while developing and sharing your visualisation.

What types of charts have you selected and why II. How have you used colour (or not).

How have you used hierarchy in your approach
What interactive components did you introduced
How have you supported the motivations of the persona you defined.

Answer:

The use of data visualization is for the development of the visual development of the data set for the understanding of the general public. The visual aids of the data set created helps in the process of showing the way the data is used in the data set. The visualization is achieved with the help of patterns, trends in data and with the help of correlation of the data. The data visualization helps in the recognition of the data easier and is achieved with the help of data visualization tools.

For the development of this blog, the data set, which has been used, is from an organization named Tully’s Coffee. The data set is composed of data that has been classified into the categories of profit and cost incurred by the company in the production of the products that they are producing. There is also the conclusion of the marketing cost that the company bears for the advertisements in the states. The data set has been divided with the help of state location of the United States of America with the help of area codes. The data set also provides an overview of the predicted values for the sales, profit, marginal cost and the cost of the goods the company requires for the production procedures. The total market size has again been divided into four quadrants according to the positioning of the states. The products that the company produces has again been divided into two classes: Caffeinated and Decaffeinated.

The table provides the reader with an overview of the working procedure of the data set. The column names of the tables in the data set has been discussed to provide the reader with the understanding of the data set.

FactTable		Data type
Profit	Profit generated measured (in $,000) = Margin - Total Expenses	Discrete Numerical Data
Margin	Net sales revenue (in $,000) = Sales - Cost of Goods	Discrete Numerical Data
Sales	Operating revenue (in $,000) earned from selling coffee/tea products	Discrete Numerical Data
COGS	Cost of Goods (in $,000) that is the direct costs attributable to the production of the goods sold by the company	Discrete Numerical Data
Total Expenses	Total costs in (in $,000) associated with managing and operating the business (COG not included)	Discrete Numerical Data
Marketing	Marketing costs (in $,000)	Discrete Numerical Data
Inventory	Total value of products and goods (in $,000) that are ready or for sale.	Discrete Numerical Data
Budget Profit	Projected profit (in $,000)	Discrete Numerical Data
Budget COGS	Projected cost of goods (in $,000)	Discrete Numerical Data
Budget Margin	Projected margin (in $,000)	Discrete Numerical Data
Budget Sales	Projected sales (in $,000)	Discrete Numerical Data
Area Code	Codes assigned to areas for the reference of the company.	Discrete ID Number Data
Product ID	Codes assigned to different products for the reference of the company	Discrete ID Number Data
Date	Dates for the year 205 and 2016, the first day of each month	Date Type Data
Area Code	Codes assigned to areas for the reference of the company	Discrete ID Number Data
State	States of the United States of America (20 Selected)	Location Data
Market	Market region (East, West, Central, South)	Discrete location Data
Market Size	Market size as a factor of population and demand (Major vs. Small)	Discrete Data
Product Type	Type of coffee or tea sold (Coffee, Espresso, Tea, Herbal Tea)	Discrete Type Data
Product	Product sub-category	Discrete Type Data
Product Id	Codes assigned to different products for the reference of the company	Discrete ID Number Data
Type	Caffeinated vs. Decaffeinated	Discrete Type Data

Based on the data set provided the following tables have been decided to be plotted for the development of the report:

Total Expenses Plotted Against Market And State
Profit Plotted Against Market And State
Sales Plotted Against Market And State
Profit Plotted Against Products
Total Expenses Plotted Against Products
Budget Cost Of Goods Plotted Against Products
Budget Margin Plotted Against Products
Budget Profit Plotted Against Products
Budget Sales Plotted Against Products
Budget Cost Of Goods Plotted Against Locations
Budget Margin Plotted Against Locations
Budget Profit Plotted Against Locations
Budget Sales Plotted Against Locations

These charts would help in providing the overview of the data set that has been provided. The columns chosen for the development of the charts will be able to provide the reader with the insight about the revenue collecting system of the company.

The data set, which is to be used for the development of this report, has been collected following all the rules and regulation of the ethical and legal problems. The law, which has been followed during the collection of the data set, is the Data Protection Act 1998. This law helps in keeping the data that has been collected safe from the hands of hackers and data theft. The ethical issues that were considered during the development of the report are as follows:

During the collection of the data, the full consent of the participants were taken. The participants were told what the data that was being collected for and the extent to which the data was to be shared on the public domain. The process of informing the participants about the extent of their data usage is an important aspect during the collection of the data. The data was collected from the participants under their full consent and they were completely willing to share their data on the public domain.
The details and the data, which the participants refrained from sharing with the collection procedures, were excluded from the data set and was not used in the data set. The data was not taken into concern when the analysis was being conducted.
The data, which was being shared on the web, was made completely anonymous for the safekeeping of the participant’s identity.
For the collection procedure of personal information, the details were collected under the law of Data Protection Act 1998. Even if there was any inclusion of personal data in the data set, the details were removed during the process of analysis.

The first dashboard developed from the data set contains three charts: Total Expenses Plotted against Market and State, Profit Plotted against Market and State and Sales Plotted against Market and State. The graphs has been developed are in the form of line chart, column chart and an area chart. The line chart shows the total expense that is incurred by the company is selling of the products in the respective markets. The highest amount of resources spent on the expenses of the resources is in the state of California. The lowest expenses has been recorded in the state of New Hampshire. On an average, the south market requires the least amount of expenses.

The second graph of the dashboard displays the profit that has been collected by the company from the sale of the products in the market categories. The highest profit that has been collected is from the state of California. This proves that the people of California use the product of Tully more than the other states of the country. The lowest profit collected is from the state of New Mexico. The value has reached as low as below the 1000 mark. All other states of the country donate a generous amount of profit. The third graph of the dashboard depicts the values of sales that the company has been able to sell in the country. California again records the highest amount of sale whereas the least amount of sale has been recorded in New Hampshire. From an over view it can be said that the south market has the lowest sale among the four markets.

The above displayed second dashboard shows the visualization of two graphs: Profit Plotted against Products and Total Expenses Plotted against Products. The charts developed for the data are in the form of line chart and column chart. The first graph of the dashboard shows the values of the profit that has been collected from the sale of the products in the country. The highest amount of profit has been gained by the product Columbian coffee. However the value of the green tea product has become too much low that it has gone to negative. The company should start making plans to make their profit collection more from the products which is able to provide them with the most amount of profit. The second graphs shows the values of the total amount of expenses that has been spent on the products. From the first graph it can be noted that the company is following the best trend in keeping the expenses in the category of the products which is providing the company with the highest profit.

The third dashboard created helps in understanding the predicted budget of the company based on product categories: Budget Cost of Goods Plotted against Products, Budget Margin Plotted against Products, Budget Profit Plotted against Products and Budget Sales Plotted against Products. The charts that has been developed for the analysis of the report are Gantt chart, line chart, column chart and heat map. From the first chart of the dashboard it can be said that the Columbian coffee has the top priority for the benefit of the future. The regular espresso product can be said to contribute the least amount of cost of the goods for the preparation of the product. The second graph depicts the use of the values of the budget margin for the products for the company.

The highest calculated value is for the product of Columbian coffee. The least values has again been found to be of green tree. The similar trend can also be seen in the third graph made with the values of the profit that has been predicted for the products. Columbian coffee has the highest amount of profit forecasted as well as the green tea is to provide the company with the least amount of profit. The last graph of the dashboard is the heat map showing the values of the predicted sales of the products in the market. The process of understanding a heat map is with the help of the saturation of the colour in the boxes. A single hue is used for the colouring of the heat map and the saturation is based on the value the respective object holds. The higher the value the darker will be the colour of the box. The trend of the highest collected value from the sale of the products has been collected form the product of Columbian coffee and the least value is for the product of regular espresso.

The final dashboard provided above shows the visualization created with the idea of showing the predicted budget with respect to the states they are currently distributing their products: Budget Cost of Goods Plotted against Locations, Budget Margin Plotted against Locations, Budget Profit Plotted against Locations and Budget Sales Plotted against Locations. This dashboard has been developed solely based on the usage of the geographical charts. The locations in the data set are corresponding to the locations on the map. The values to the corresponding locations are summed up and used as a reference value for colouring the locations.

The saturation of the colour is based on the value of the location: higher the value of the location the darker will be the colour of the location on the map. The dashboard has the values of the products similar to the previous dashboard with the exception that the values has been plotted against the location of the sale of the products rather than the use of the product categories. From the first chart it can be seen that the state of California provides the highest predicted value for the cost of goods in the country. The least value of the cost of goods can be said to be contributed from the location of the central states of the country provide the company with an average amount of cost for the goods to be used for the production of the goods.

The similar trend has been followed in the next chart where the maximum predicted margin has been set for the state of California and the least can be said to be provided by the state of New Mexico. On an average the coastal states provide an average value to the predicted margin of the products in the states. From the third chart of the dashboard it can be said that the values of the state of California has the highest predicted profit for the country. It would be beneficial for the company for investing their resources in the production of the products in the state of California. The least amount of profit has been predicted for the state of New Mexico.

The last chart of the dashboard uses the value of the predicted sales to be plotted in the chart. The state of California still shows the highest value in terms of predicted sales for the company’s products. The least amount of value has again been found to be form the state of New Mexico. The overall study of the dashboard shows that the state of California is the best state in the United States of America for the country to pursue their company’s trade for the maximum benefit.