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NEW QUESTION # 67
A consultant updates an IF-THEN calculation to use a newly created calculated field "Last Name" (parsed from "Full Name"). After the change, performance becomes noticeably worse.
Which two options should the consultant use to improve dashboard performance without altering functionality? Choose two.
Answer: A,B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The performance degradation originates from string parsing inside Tableau ("last word of Full Name") and then feeding that calculated field into another row-level IF-THEN calculation.
This creates:
* Nested calculations
* High per-row evaluation load
* Slow extract query performance or slow live query generation
Tableau documentation recommends two best-practice approaches:
Solution 1: Precompute the "Last Name" field upstream (Option C)
When the parsing is performed in:
* The database
* ETL/ELT pipelines
* Tableau Prep
then Tableau Desktop receives a clean field with no runtime computation needed.
This significantly reduces row-level calculation burden.
Solution 2: Replace Quick Filters with Action Filters (Option A)
Quick filters are expensive because Tableau:
* Runs additional queries to populate filter controls
* Re-queries every time the filter changes
Action Filters run directly from the visualization and are far more performant.
This improves the overall dashboard performance without changing logic.
Why the other options are incorrect:
B). Calculate "Last Name" inside the IF THEN calculation
This makes the expression even more complex - worse performance.
D). Change to a CASE statement
CASE does not improve performance when the heavy part of the logic is the string parsing, not the IF-THEN structure.
Thus, A and C are the correct performance-improving choices.
* Performance guidance recommending upstream computation of string fields
* Filter optimization best practices encouraging Action Filters over Quick Filters
* Extract runtime cost reduction strategies
NEW QUESTION # 68
A multi-national company wants to have a Tableau dashboard that will provide country-level information for both its forecast summaries and year-on-year metrics. The company wants to toggle between these two views while leaving main key performance indicators (KPIs) visible on the main dashboard.
Which method is the most efficient in achieving the company's requirements?
Answer: A
Explanation:
. Add the calculated fields as a Detail under the Marks card of the floating view, create a "Change Parameter" action, and set the
"Target Parameter" and "Source Fields" to the parameter and calculated field you created.
. Check the box for "Control visibility using value" in the Layout tab of the floating view and select the parameter you created.
Explanation:
The most efficient method for toggling between two views (forecast summaries and year-on-year metrics) while keeping main KPIs visible involves using a parameter and calculated fields for controlling visibility:
Create a Boolean Parameter: This parameter will have two aliases representing the two views ("Forecast View" and "Year-on-Year View"). This allows the user to select which view they wish to see directly from the dashboard.
Calculated Field: Create a calculated field that always returns True. This field acts as a constant placeholder to enable the visibility control tied to the parameter.
Dashboard Setup: Place both the forecast summary and the year-on-year metrics sheets on the dashboard. Set the year-on-year metrics sheet as a floating object over the forecast summary.
Visibility Control: Use the "Control visibility using value" option in the Layout tab for the floating year-on-year metrics view. Tie this setting to the Boolean parameter so that changing the parameter will show or hide this view without affecting the main KPIs displayed on the dashboard.
Interactivity: Implement a "Change Parameter" dashboard action where selecting different options in the dashboard (e.g., clicking on certain parts) triggers the parameter to change, thus toggling the visible view.
References
This method leverages Tableau's dashboard interactivity features including parameters, calculated fields, and visibility settings, as recommended in Tableau's user guide on dynamic dashboard design.
NEW QUESTION # 69
From the desktop, open the CC workbook.
Open the City Pareto worksheet.
You need to complete the Pareto chart to show the percentage of sales compared to the percentage of cities.
The chart must show references lines to visualize how the data compares to the Pareto principle.
From the File menu in Tableau Desktop, click Save.
Answer:
Explanation:
See the complete Steps below in Explanation:
Explanation:
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.
References:
Tableau Help: Offers detailed guidance on creating Pareto charts and adding reference lines.
Tableau Visualization Best Practices: Provides tips on effectively displaying cumulative data and principles such as Pareto.
By following these steps, you will have successfully enhanced the City Pareto worksheet to include a complete Pareto chart with reference lines that illustrate how the sales data compares to the Pareto principle, making it easier to analyze and communicate the distribution of sales across cities.
NEW QUESTION # 70
A client is concerned that a dashboard has experienced degraded performance after they added additional quick filters. The client asks a consultant to improve performance.
Which two actions should the consultant take to fulfill the client's request? Choose two.
Answer: C,D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Quick filters are one of the most expensive features in Tableau because they require queries to populate value lists and dynamic recalculations when filters change.
According to Tableau performance documentation:
1. Add an "Apply" Button
This prevents Tableau from re-running queries every time the user selects a filter value.
Queries are executed once when the user presses Apply.
This is a documented best practice for filter-heavy dashboards.
2. Replace Quick Filters with Filter Actions
Filter actions are far more efficient because:
* They leverage the existing view context
* They do not require separate filter UI queries
* They avoid the overhead of quick filter value lists
Tableau recommends using filter actions instead of multiple quick filters for better performance.
Why the other options are incorrect:
* B. Add filters to Context: Context filters make downstream filters faster, but do not reduce quick filter processing cost; they can even increase extract size and slow down the dashboard.
* C. Only Relevant Values: This actually slows performance because Tableau must re-evaluate the entire data set to determine relevancy every time filters update.
Thus, A and D are the correct performance-improvement approaches.
* Tableau Performance Checklist recommending Apply button for multi-select filters.
* Performance documentation advising the use of Filter Actions over multiple quick filters.
* Filtering best practices explaining the cost of Only Relevant Values.
NEW QUESTION # 71
A client wants to flag orders that have sales higher than the regional average.
Which calculated field will produce the required result?
Answer: A
Explanation:
To flag orders with sales higher than the regional average, the correct calculated field would compare the sum of sales for each order against the average sales of all orders within the same region:
Correct Formula: { FIXED [Order ID] : SUM([Sales]) } > { FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) } This calculation uses a Level of Detail (LOD) expression:
The left part of the formula { FIXED [Order ID] : SUM([Sales]) } calculates the total sales for each individual order.
The right part { FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) } calculates the average sales per order within each region.
The > operator is used to compare these two values to determine if the sales for each order exceed the regional average.
References
This formula utilizes Tableau's LOD expressions to perform complex comparisons across different dimensions of the data, as explained in Tableau's official training materials on LOD calculations.
NEW QUESTION # 72
......
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