Assignment Prompt & Instructions
Follow the attached instructions to complete this work also find the previous work attach to it.
– ## DVDiscussion2.docx
– ## Previouswork.docx
**## DVDiscussion2.docx**
Deconstructions of an Advanced Dashboard: Dashboard Approach and Storytelling
**Task**
There is a discussion you will need to participate in this unit. Select the button that follows to access the discussion thread.
You will be using the same dashboard that you discussed in the previous unit’s discussion.
**Discussion Prompts**
· What dashboard approach do you think the dashboard creator used? (Review the four approaches on page 225 of the Milligan book.) (one paragraph)
· Do you think the dashboard creator has adequately told a story? Do you think they left something out of their dashboard? (one paragraph)
· What interactive elements did the dashboard designer add, for example, highlights, filters, and URLs? Did they use sheet swap? Do you think they were effective? If they did not add these, what would have been helpful? (one paragraph)
· Provide a screenshot of the screen you selected and a link to the webpage on the Viz of the Day site.
I m going to attach the previous work.
**## Previouswork.docx**
This CRM Sales Dashboard gives an overall view of the level of sales per manager, agent, product, region, and segment in a business dealing with computer hardware. It focuses on some of the major metrics which are a total revenue, deal close time, and win/loss ratio, which allows the decision-maker to know top and bottom performers, sales trends in different areas, and product or sector-wise revenue contribution. It is relevant to enhance a strategy in sales and the allocation of resources as well as warm tracking. The issue it solves is the unavailability to provide customers with real-time actionable influences over the sales effectiveness. The main audience is the sales managers, executives and business analysts who investigate data-driven decisions (Chauhan, 2025).
**Justification for the selection of CRM Sales dashboard**
The reason I have chosen this dashboard is that of its distinct structure and the diversity of knowledge the latter offers at the same glance. It is logically and conveniently designed to aggregate the most significant measures, performance analysis, and geographical observations, therefore, presenting an appealing and convenient ease of analysis. The use of heat maps, bar and map plot concentrated the depth such that it is appealing to study the trends in performances of the sales across various territories, and representatives as well as products.
**Visualizations**
The dashboard is comprised of multiple forms of visualizations that are utilized to display sales data effectively.
_Heatmap_: A heatmap shows quarterly revenue by manager and how that revenue has performed across time using color intensity as an indicator. It facilitates in knowing which managers are performing well and worst in certain quarters with a single look.
_Vertical bar chart_: Individual sales agents can reflect on how revenue varies which is compared by a vertical bar chart that is arranged to reflect the best performers and thus it becomes easy to determine individual contribution.
_Map_: A symbol map visualizes revenue by country, with darker shades meaning more sales; it makes the difference in performance easy to see, showing, e.g., the superiority of the U.S. market.
_Bubble chart_: Information on won versus loss deals by product category is compared on a bubble chart; the bubble size and intensity determine the performance, but the actual measure of the size could be explained.
_Bar chart_: Lastly, one bar chart indicates revenue by business sector with average represented by a dotted line, hence providing an easy comparison of how each of the business sectors is performing relative to set standards.
The graphics used have combined effect of painting a balanced picture of sales people, product, place, and section. They all are well labeled and clear though a more elaboration on how they calculate the sizing of the bubble chart helps (Burnay et al., 2019). Overall, the dashboard can be characterized as relatively prudent and visual-oriented in its approach to the performance analysis.
**Filters**
The dashboard creator has provided clear filter to provide more interactivity and the possibility of users to sort the data view. At the top of the dashboard one can find dropdown filters with the options of “Country” and “Region Office”, through which the user can filter the data shown in all charts and visuals by geographic criteria. Such filters allow the user to target markets or the sales territories so that it is less cumbersome to analyse the performance at regional or national levels. Although it is only two filters in view, it seems to dynamically refresh the whole dashboard. This application of filters increases usability in that one can make succinct insights, without overwhelming the user.
**Selected screen**
****
****Link to the webpage:****
**[https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard](https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard)**
****References****
**Burnay, C., Dargam, F., & Zarate, P. (2019). Data visualization for decision-making: an important issue.**
**_Operational Research_,**
**_19_(4), 853-855.**
**[https://link.springer.com/article/10.1007/s12351-019-00530-z](https://link.springer.com/article/10.1007/s12351-019-00530-z)**
**Chauhan, K (2025). Computer hardware sales opportunities dashboard [Dashboard].**
**_Public Tableau_.**
**[https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard](https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard)**
**·**
**[image.png](https://learn.umgc.edu/d2l/le/1384121/discussions/posts/108657074/ViewAttachment?fileId=107241806)**
**(181.82 KB)**
**## image1.png**
**## Previouswork.docx**
This CRM Sales Dashboard gives an overall view of the level of sales per manager, agent, product, region, and segment in a business dealing with computer hardware. It focuses on some of the major metrics which are a total revenue, deal close time, and win/loss ratio, which allows the decision-maker to know top and bottom performers, sales trends in different areas, and product or sector-wise revenue contribution. It is relevant to enhance a strategy in sales and the allocation of resources as well as warm tracking. The issue it solves is the unavailability to provide customers with real-time actionable influences over the sales effectiveness. The main audience is the sales managers, executives and business analysts who investigate data-driven decisions (Chauhan, 2025).
**Justification for the selection of CRM Sales dashboard**
The reason I have chosen this dashboard is that of its distinct structure and the diversity of knowledge the latter offers at the same glance. It is logically and conveniently designed to aggregate the most significant measures, performance analysis, and geographical observations, therefore, presenting an appealing and convenient ease of analysis. The use of heat maps, bar and map plot concentrated the depth such that it is appealing to study the trends in performances of the sales across various territories, and representatives as well as products.
**Visualizations**
The dashboard is comprised of multiple forms of visualizations that are utilized to display sales data effectively.
_Heatmap_: A heatmap shows quarterly revenue by manager and how that revenue has performed across time using color intensity as an indicator. It facilitates in knowing which managers are performing well and worst in certain quarters with a single look.
_Vertical bar chart_: Individual sales agents can reflect on how revenue varies which is compared by a vertical bar chart that is arranged to reflect the best performers and thus it becomes easy to determine individual contribution.
_Map_: A symbol map visualizes revenue by country, with darker shades meaning more sales; it makes the difference in performance easy to see, showing, e.g., the superiority of the U.S. market.
_Bubble chart_: Information on won versus loss deals by product category is compared on a bubble chart; the bubble size and intensity determine the performance, but the actual measure of the size could be explained.
_Bar chart_: Lastly, one bar chart indicates revenue by business sector with average represented by a dotted line, hence providing an easy comparison of how each of the business sectors is performing relative to set standards.
The graphics used have combined effect of painting a balanced picture of sales people, product, place, and section. They all are well labeled and clear though a more elaboration on how they calculate the sizing of the bubble chart helps (Burnay et al., 2019). Overall, the dashboard can be characterized as relatively prudent and visual-oriented in its approach to the performance analysis.
**Filters**
The dashboard creator has provided clear filter to provide more interactivity and the possibility of users to sort the data view. At the top of the dashboard one can find dropdown filters with the options of “Country” and “Region Office”, through which the user can filter the data shown in all charts and visuals by geographic criteria. Such filters allow the user to target markets or the sales territories so that it is less cumbersome to analyse the performance at regional or national levels. Although it is only two filters in view, it seems to dynamically refresh the whole dashboard. This application of filters increases usability in that one can make succinct insights, without overwhelming the user.
**Selected screen**
****
****Link to the webpage:****
**[https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard](https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard)**
****References****
**Burnay, C., Dargam, F., & Zarate, P. (2019). Data visualization for decision-making: an important issue.**
**_Operational Research_,**
**_19_(4), 853-855.**
**[https://link.springer.com/article/10.1007/s12351-019-00530-z](https://link.springer.com/article/10.1007/s12351-019-00530-z)**
**Chauhan, K (2025). Computer hardware sales opportunities dashboard [Dashboard].**
**_Public Tableau_.**
**[https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard](https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard)**
**·**
**[image.png](https://learn.umgc.edu/d2l/le/1384121/discussions/posts/108657074/ViewAttachment?fileId=107241806)**
**(181.82 KB)**
**## image1.png**
**## DVDiscussion2.docx**
Deconstructions of an Advanced Dashboard: Dashboard Approach and Storytelling
**Task**
There is a discussion you will need to participate in this unit. Select the button that follows to access the discussion thread.
You will be using the same dashboard that you discussed in the previous unit’s discussion.
**Discussion Prompts**
· What dashboard approach do you think the dashboard creator used? (Review the four approaches on page 225 of the Milligan book.) (one paragraph)
· Do you think the dashboard creator has adequately told a story? Do you think they left something out of their dashboard? (one paragraph)
· What interactive elements did the dashboard designer add, for example, highlights, filters, and URLs? Did they use sheet swap? Do you think they were effective? If they did not add these, what would have been helpful? (one paragraph)
· Provide a screenshot of the screen you selected and a link to the webpage on the Viz of the Day site.
I m going to attach the previous work.
**## Previouswork.docx**
This CRM Sales Dashboard gives an overall view of the level of sales per manager, agent, product, region, and segment in a business dealing with computer hardware. It focuses on some of the major metrics which are a total revenue, deal close time, and win/loss ratio, which allows the decision-maker to know top and bottom performers, sales trends in different areas, and product or sector-wise revenue contribution. It is relevant to enhance a strategy in sales and the allocation of resources as well as warm tracking. The issue it solves is the unavailability to provide customers with real-time actionable influences over the sales effectiveness. The main audience is the sales managers, executives and business analysts who investigate data-driven decisions (Chauhan, 2025).
**Justification for the selection of CRM Sales dashboard**
The reason I have chosen this dashboard is that of its distinct structure and the diversity of knowledge the latter offers at the same glance. It is logically and conveniently designed to aggregate the most significant measures, performance analysis, and geographical observations, therefore, presenting an appealing and convenient ease of analysis. The use of heat maps, bar and map plot concentrated the depth such that it is appealing to study the trends in performances of the sales across various territories, and representatives as well as products.
**Visualizations**
The dashboard is comprised of multiple forms of visualizations that are utilized to display sales data effectively.
_Heatmap_: A heatmap shows quarterly revenue by manager and how that revenue has performed across time using color intensity as an indicator. It facilitates in knowing which managers are performing well and worst in certain quarters with a single look.
_Vertical bar chart_: Individual sales agents can reflect on how revenue varies which is compared by a vertical bar chart that is arranged to reflect the best performers and thus it becomes easy to determine individual contribution.
_Map_: A symbol map visualizes revenue by country, with darker shades meaning more sales; it makes the difference in performance easy to see, showing, e.g., the superiority of the U.S. market.
_Bubble chart_: Information on won versus loss deals by product category is compared on a bubble chart; the bubble size and intensity determine the performance, but the actual measure of the size could be explained.
_Bar chart_: Lastly, one bar chart indicates revenue by business sector with average represented by a dotted line, hence providing an easy comparison of how each of the business sectors is performing relative to set standards.
The graphics used have combined effect of painting a balanced picture of sales people, product, place, and section. They all are well labeled and clear though a more elaboration on how they calculate the sizing of the bubble chart helps (Burnay et al., 2019). Overall, the dashboard can be characterized as relatively prudent and visual-oriented in its approach to the performance analysis.
**Filters**
The dashboard creator has provided clear filter to provide more interactivity and the possibility of users to sort the data view. At the top of the dashboard one can find dropdown filters with the options of “Country” and “Region Office”, through which the user can filter the data shown in all charts and visuals by geographic criteria. Such filters allow the user to target markets or the sales territories so that it is less cumbersome to analyse the performance at regional or national levels. Although it is only two filters in view, it seems to dynamically refresh the whole dashboard. This application of filters increases usability in that one can make succinct insights, without overwhelming the user.
**Selected screen**
****
****Link to the webpage:****
**[https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard](https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard)**
****References****
**Burnay, C., Dargam, F., & Zarate, P. (2019). Data visualization for decision-making: an important issue.**
**_Operational Research_,**
**_19_(4), 853-855.**
**[https://link.springer.com/article/10.1007/s12351-019-00530-z](https://link.springer.com/article/10.1007/s12351-019-00530-z)**
**Chauhan, K (2025). Computer hardware sales opportunities dashboard [Dashboard].**
**_Public Tableau_.**
**[https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard](https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard)**
**·**
**[image.png](https://learn.umgc.edu/d2l/le/1384121/discussions/posts/108657074/ViewAttachment?fileId=107241806)**
**(181.82 KB)**
**## image1.png**
**## DVDiscussion2.docx**
Deconstructions of an Advanced Dashboard: Dashboard Approach and Storytelling
**Task**
There is a discussion you will need to participate in this unit. Select the button that follows to access the discussion thread.
You will be using the same dashboard that you discussed in the previous unit’s discussion.
**Discussion Prompts**
· What dashboard approach do you think the dashboard creator used? (Review the four approaches on page 225 of the Milligan book.) (one paragraph)
· Do you think the dashboard creator has adequately told a story? Do you think they left something out of their dashboard? (one paragraph)
· What interactive elements did the dashboard designer add, for example, highlights, filters, and URLs? Did they use sheet swap? Do you think they were effective? If they did not add these, what would have been helpful? (one paragraph)
· Provide a screenshot of the screen you selected and a link to the webpage on the Viz of the Day site.
I m going to attach the previous work.
**## Previouswork.docx**
This CRM Sales Dashboard gives an overall view of the level of sales per manager, agent, product, region, and segment in a business dealing with computer hardware. It focuses on some of the major metrics which are a total revenue, deal close time, and win/loss ratio, which allows the decision-maker to know top and bottom performers, sales trends in different areas, and product or sector-wise revenue contribution. It is relevant to enhance a strategy in sales and the allocation of resources as well as warm tracking. The issue it solves is the unavailability to provide customers with real-time actionable influences over the sales effectiveness. The main audience is the sales managers, executives and business analysts who investigate data-driven decisions (Chauhan, 2025).
**Justification for the selection of CRM Sales dashboard**
The reason I have chosen this dashboard is that of its distinct structure and the diversity of knowledge the latter offers at the same glance. It is logically and conveniently designed to aggregate the most significant measures, performance analysis, and geographical observations, therefore, presenting an appealing and convenient ease of analysis. The use of heat maps, bar and map plot concentrated the depth such that it is appealing to study the trends in performances of the sales across various territories, and representatives as well as products.
**Visualizations**
The dashboard is comprised of multiple forms of visualizations that are utilized to display sales data effectively.
_Heatmap_: A heatmap shows quarterly revenue by manager and how that revenue has performed across time using color intensity as an indicator. It facilitates in knowing which managers are performing well and worst in certain quarters with a single look.
_Vertical bar chart_: Individual sales agents can reflect on how revenue varies which is compared by a vertical bar chart that is arranged to reflect the best performers and thus it becomes easy to determine individual contribution.
_Map_: A symbol map visualizes revenue by country, with darker shades meaning more sales; it makes the difference in performance easy to see, showing, e.g., the superiority of the U.S. market.
_Bubble chart_: Information on won versus loss deals by product category is compared on a bubble chart; the bubble size and intensity determine the performance, but the actual measure of the size could be explained.
_Bar chart_: Lastly, one bar chart indicates revenue by business sector with average represented by a dotted line, hence providing an easy comparison of how each of the business sectors is performing relative to set standards.
The graphics used have combined effect of painting a balanced picture of sales people, product, place, and section. They all are well labeled and clear though a more elaboration on how they calculate the sizing of the bubble chart helps (Burnay et al., 2019). Overall, the dashboard can be characterized as relatively prudent and visual-oriented in its approach to the performance analysis.
**Filters**
The dashboard creator has provided clear filter to provide more interactivity and the possibility of users to sort the data view. At the top of the dashboard one can find dropdown filters with the options of “Country” and “Region Office”, through which the user can filter the data shown in all charts and visuals by geographic criteria. Such filters allow the user to target markets or the sales territories so that it is less cumbersome to analyse the performance at regional or national levels. Although it is only two filters in view, it seems to dynamically refresh the whole dashboard. This application of filters increases usability in that one can make succinct insights, without overwhelming the user.
**Selected screen**
****
****Link to the webpage:****
**[https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard](https://public.tableau.com/app/profile/fathima.shanavas/viz/CRMSalesDashboard_17405967603400/SalesDashboard)**
****References****
**Burnay, C., Dargam, F., & Zarate, P. (2019). Data visualization for decision-making: an important issue.**
**_Operational Research_,**
**_19_(4), 853-855.**
**[https://link.springer.com/article/10.1007/s12351-019-00530-z](https://link.springer.com/article/10.1007/s12351-019-00530-z)**
**Chauhan, K (2025). Computer hardware sales opportunities dashboard [Dashboard].**
**_Public Tableau_.**
**[https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard](https://public.tableau.com/app/profile/karan.chauhan7021/viz/CRMSalesDashboard/CRMDashboard)**
**·**
**[image.png](https://learn.umgc.edu/d2l/le/1384121/discussions/posts/108657074/ViewAttachment?fileId=107241806)**
**(181.82 KB)**
**## image1.png**
– 1
– 2