Analytics-Con-301 Exam Dumps : Salesforce Certified Tableau Consultant

To complete the Pareto chart in the "City Pareto" worksheet of your Tableau Desktop and add reference lines to illustrate how the data compares to the Pareto principle, follow these steps:

Open the CC Workbook and Access the Worksheet:

From the desktop, double-click on the CC workbook to open it in Tableau Desktop.

Navigate to the City Pareto worksheet by selecting its tab at the bottom of the window.

Construct the Pareto Chart:

Ensure that sales data is aggregated by city. If not, drag the 'City' dimension to the Columns shelf and the 'Sales' measure to the Rows shelf.

Sort the sales data in descending order to properly align the cities according to their sales contribution.

To create a running total of sales, right-click on the 'Sales' measure on the Rows shelf, select 'Quick Table Calculation', and choose 'Running Total'.

Drag the 'Number of Records' field to the Rows shelf next to the Sales running total. Right-click on it, select 'Quick Table Calculation', and choose 'Running Total'. Set its calculation to 'Percent of Total' from the 'Edit Table Calculation' option to represent the percentage of cities.

Add Reference Lines for the Pareto Principle:

Click on the Analytics tab in the sidebar.

Drag a 'Reference Line' element and drop it onto the chart area.

Set the Reference Line for the Sales axis at 80% to represent the typical Pareto cutoff where 80% of effects come from 20% of causes.

Add another Reference Line on the axis representing the percentage of cities, set at 20%, to visually assess the Pareto principle.

Adjust the Appearance of the Chart:

Format the reference lines by right-clicking on them, selecting 'Edit', and choosing a distinct style or color to make them stand out.

Ensure the chart is clear and labels are appropriately adjusted for easy understanding of the data visualization.

Save Your Changes:

From the File menu, click 'Save' to ensure all your changes are stored.

To improve the performance of a Tableau workbook, it is best practice to streamline the data being used. This can be achieved by using filters to limit the data to only what is necessary for analysis, hiding fields that are not being used to reduce the complexity of the data model, and aggregating values to simplify the data and reduce the number of rows that need to be processed. These steps can help reduce the load on the server and improve the speed of the workbook.

Comprehensive and Detailed Explanation From Exact Extract:

The client wants to always show the most recent day present in the data, not today’s date. The dataset is updated intermittently, meaning some days may have no new rows. Tableau documentation states that:

Using TODAY() recalculates on every query and prevents effective caching because Tableau must compute the current date for each refresh.

Using Relative Date Filters like “Last 1 day” also prevents caching because Tableau evaluates relative conditions each time the workbook loads.

Quick Filters also break caching and decrease performance because they require interactive evaluation on each render.

A FIXED LOD calculation allows Tableau to compute the maximum date inside the extract, which preserves caching because it is data-driven, not time-driven.For example:{ FIXED : MAX([Date]) }Then filtering where [Date] = { FIXED : MAX([Date]) } ensures only the most recent date in the dataset is shown.

Tableau’s documentation on performance emphasizes that caching is maximized when calculations depend only on the data itself and not on functions like TODAY() or relative filters.

A FIXED LOD provides the best caching performance and correctly returns the most recent date based on the dataset rather than the current system date.

Tableau extract caching behavior describing how data-dependent filters cache better than time-dependent filters.

LOD Expressions guidance recommending FIXED for identifying values like “latest date in the dataset.”

Tableau performance guidelines discouraging TODAY() and relative date filters when caching is important.