Various Dashboards
I have been exploring Tableau a lot recently. I enjoyed completing the learning path “Build Your Tableau Skills” from LinkedIn Learning. The “Tableau Essential Training” by Curtis Frye helped me to brush up the foundational skills for Tableau. The “Creating Interactive Dashboards” by Matt Francis highlighted the importance of identifying who is the dashboard for, where is the dashboard viewed, why am I making the dashboard and what question am I answering with the dashboard.
After completing the learning path, I created four kinds of dashboards – exploratory dashboard (https://lnkd.in/gyQCxK4d) , an informative dashboard (https://lnkd.in/gJdny_52) , a data story (https://lnkd.in/gfqy7EwW) and a KPI dashboard (https://lnkd.in/g4mMCbve)
Customer Lifetime Value Matrix (CLTV) is frequently used in marketing and retail industries to understand the value of each customer. Specifically, the interesting insights come when you scan vertically and see that your initiatives are paying off and customers of the same relative age are spending more money.
Sales KPI Dashboard
A KPI Dashboard is used to highlight important details, to capture the users attention. It clearly shows if things are in place or not. It generally doesn’t have any filtering or interaction. Usually a KPI dashboard compares the current value to the target or the historic value. In the below KPI dashboard, I have shown sales over time for each region and the bar chart shows the sales of the current year for the selected month compared with the sales of the previous year for the selected month. This clearly shows the comparison between similar times and we know if the sales is good or bad compared to the previous year. Explore the KPI dashboard on Tableau Public.
Exploratory dashboard
An exploratory dashboard helps to explore the dataset. It includes various sheets. The data is presented in a simple way so that it is easy for the users to find answers to their questions. Generally, an exploratory dashboard has a high level of interaction. Using the filters, actions and highlights the users will be able to drilldown into the data. In the exploratory dashboard I created, the user can examine the the sales and profits for the past three years, see the regional variations, search for high and low periods and also identify good and bad customers. This dashboards has filters, actions and highlights enabled, so the user can click on any data point to get a better look at the data. Visit the Exploratory dashboard in Tableau Public to get the interactive view.
Informative Dashboard
An informative dashboard is all about specific information. I will explore and the present the data in a way that it is easy to find the answers. There will a little bit of interaction but the dashboard will be focused on answering the question rather than letting the users to explore and find the answers. I examined the technology sales data for New York, how many sales happened in each city and identified good and bad customers. From the dashboard, any city can be clicked to drilldown to specific details for that city, any sub-category can be clicked to show the top products in that sub-category. Visit the informative dashboard in Tableau Public for an interactive view.
Data Story
A data story is used to share specific insights in a storytelling manner. It generally has multiple dashboards presented into a narrative and ending with an ‘aha’ moment. In the data story that I created, I initially show the sales and profit over time. If you have a look at the dashboard, I have highlighted the two data points that had peak sales
Next, I wanted to show the specific sub-category that contributed the spike in sales. So I have shown the sub-category and regional chart for sales. I identified that that Machine sales in the South region contributed to the spike in sales.
After this, I went back to the sales and profit over time and identified two instances where profits peaked and fell down in a similar manner.
Next, I showed the drilldown for these two instances. We can see that the technology category majorly contributed to the peak and fall of the profits.
