![]() → Create another Parameter Action, named Update Sales Parameter. From the Source sheets select Profit Slider, from the Run Action -> Select, from the Target Parameter select Profit Parameter and from the field select Profit per Order (bin) and for Aggregation select None. Name this action Update Profit parameter. ![]() → Go to Dashboard -> Actions -> Add Action -> Change Parameter. → Create a Dashboard with the Profit Slider, Sales Slider and Sales vs Profit Sheets. → Drag the calculated field Quadrant on Colour and Order ID on Detail. IF SUM()> and SUM()> THEN ‘High Sales/High Profit’ĮLSEIF SUM()> and SUM() THEN ‘Low Sales/High Profit’ → Create a calculated field named Quadrant with the formula: From the Marks Area change the visualization type to Circle. Drag the Sales on Columns and Profit on Rows. → Create a new Sheet named Sales vs Profit. → Change the visualization type for Sales per Order (bin) to line and for the Sales Parameter to Circle. Right click on Sales per Order (bin) and select Continuous. Drag the Sales per Order (bin) and Sales Parameter on Columns. → Change the visualization type for Profit per Order (bin) to line and for the Profit Parameter to Circle. Right click on Profit per Order (bin) and select Continuous. Drag the Profit per Order (bin) and Profit Parameter on Rows. → Create a new Sheet named Profit Slider. From the Data type select Integer and for the Current Value type in a value, for example 8539. → Create a parameter named Sales Parameter. From the Data type select Integer and for the Current Value type in a value, for example -2471. → Create a parameter named Profit Parameter. → Right click on the Sales per Order calculated field and select Create -> Bins. → Right click on the Profit per Order calculated field and select Create -> Bins. → Create a calculated field named Sales per Order with the formula: → Create a calculated field named Profit per Order with the formula: → In Tableau Desktop, connect to Superstore sample data provided by Tableau. Next, we will build a Scatter Plot chart and we will show you all the necessary steps you need to do in order to add custom sliders and more interactivity to your analysis. In the visualization below we chose to use both calculated fields and parameters to identify profit and sales values in several situations: lower sales, but higher profit, higher sales, but lower profit, higher sales and higher profit, lower sales and lower profit. We can also add calculated fields or parameters to provide clarity in the data and to segment information relevant to us. Of course, Scatter Plot visualizations can be customized with other data analysis elements in Tableau, such as reference lines or trend lines to identify the information we are interested in more quickly. For example, the Scatter Plot chart helps us quickly identify which sales generated the highest or lowest profit. The main role of this graph is to highlight the data outliers, along with the correlations between the analyzed measures. ![]() Later, dimensions can be added for a better understanding of the data and for a complete visualization of them. Scatter Plot is a chart that displays the correlations between two measures in a single visualization. But first, let’s see what this type of chart is and how it can be improved with more. The Scatter Plot graph helps users to visualize and understand the distribution of measures in relation to others. For consumer goods companies, data analysis on sales profitability plays an essential role in establishing future sales or marketing strategies. In today’s article we will discuss how to build a Scatter Plot chart and how to add custom sliders to provide interactivity to our analysis.Īs we said, Tableau offers us countless possibilities to visualize our data. One of the most popular types of graphics in Tableau is Scatter Plot. Tableau Software is a complex data analysis and visualization tool that offers users unlimited possibilities for data exploration and understanding. Profit margins, sales margins depending on product categories, inventory situation or number of customers are some of the metrics that must be followed for an in-depth analysis of how the company works. For retail, consumer goods or eCommerce companies, data analytics is a vital element.
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