Free Salesforce Analytics-Con-301 Exam Dumps April 2026

Comprehensive and Detailed Explanation From Exact Extract:

Key details from the scenario:

The dashboard is on a command center screen.

The environment cannot access the internet.

The data source is real-time (live).

The dashboard must keep itself refreshed automatically.

No human interaction should be required.

From Tableau's documentation:

Dashboard Extension API

Tableau's Extension API allows developers to create custom extensions that can automate refreshing a live dashboard at intervals.

The extension is hosted on the company's internal web server, which solves the ''no internet access'' limitation.

This is the only method in the listed options that:

Works offline

Can auto-refresh the dashboard

Supports a ''screen-based'' live monitoring use case

Uses the existing live connection (no need for extracts)

Thus, A is correct.

Why the other options are wrong:

B. Schedule a Prep Flow

Prep flows do not refresh dashboards.

They only refresh prepared data sources.

The dashboard still won't auto-update unless reopened.

C. Download an extension from Tableau Exchange

Tableau Exchange requires internet access, which the company does not have.

Also, ''sandboxed extensions'' cannot refresh the dashboard at timed intervals.

D. Use extracts and scheduled extract refresh

Extracts require:

A Tableau Server / Cloud schedule

Internet access for Cloud

And extracts are not real-timeThis contradicts the requirement for real-time data and an offline environment.

Comprehensive and Detailed Explanation From Exact Extract:

The key detail of the question:

''filter out particular categories, but wants the percent of total calculation to remain steady even as they filter items in or out.''

This means the percent of total must ignore filters.

Table calculations always operate after filters, except table calc filters like 'Filter on Table Calculation,' and after dimension filters, so filtering categories directly will change the denominator.

Tableau's documented solution for ''percent of total that does not change with filtering'' is:

Use a FIXED LOD to define the stable denominator

A FIXED LOD expression ''freezes'' the aggregation level and is unaffected by dimension filters unless explicitly added to context.

This allows the consultant to compute:

{ FIXED : SUM([Sales]) }

or

{ FIXED [Category] : SUM([Sales]) }

Then percent of total becomes:

SUM([Sales]) / { FIXED : SUM([Sales]) }

The FIXED LOD stores the total before filters are applied, ensuring the percent remains steady.

This is exactly what Tableau documentation explains under:

Level of Detail Expressions

LODs and Order of Operations

Using LODs to create filter-independent calculations

Thus, D is correct.

Why the other answers are wrong:

A. Context Filter

Context filters run before FIXED LODs but after raw data.

If Category is put into context, LOD totals would be reduced.

Table calculation totals still change because table calcs run near the bottom of the pipeline.

B. Data Source Filter

Data source filters remove rows before all table calculations and LODs.

This would make the percent of total incorrect, because filtered-out categories would physically be gone.

C. Aggregate Expression

An aggregate field alone does not solve the issue because it still respects dimension filters.

To record the performance of the Property Transactions dashboard in the NYC Property Transactions.twbx workbook and analyze it using a bar chart, follow these detailed steps:

Open the NYC Property Transactions Workbook:

From the desktop, double-click the NYC Property Transactions.twbx workbook to open it in Tableau Desktop.

Start Performance Recording:

Before doing anything else, navigate to the 'Help' menu in Tableau Desktop.

Select 'Settings and Performance', then choose 'Start Performance Recording'.

Open the Property Transactions Dashboard and Reset Filters:

Navigate to the Property Transactions dashboard within the workbook.

Reset all filters to show all values. This usually involves selecting the dropdown on each filter and choosing 'All' or using a 'Reset' button if available.

Stop the Performance Recording:

Go back to the 'Help' menu.

Choose 'Settings and Performance', then select 'Stop Performance Recording'.

Tableau will automatically open a new tab displaying the performance recording results.

Save the Performance Recording:

In the performance recording results tab, go to the 'File' menu.

Click 'Save As' and navigate to the C:\CC\Data\ directory.

Save the file, ensuring it is stored in the desired location.

Create a New Worksheet for Performance Analysis:

Return to the NYC Property Transactions workbook and create a new worksheet by clicking on the 'New Worksheet' icon.

Drag the 'Command Name' field to the Columns shelf.

Drag the 'Elapsed Time' field to the Rows shelf.

Ensure that the 'Worksheet' field is also included in the analysis to break down the time by individual sheets within the dashboard.

Choose 'Bar Chart' from the 'Show Me' options to display the data as a bar chart.

Customize and Finalize the Bar Chart:

Adjust the axes and labels to clearly display the information.

Format the chart to enhance readability, applying color coding or sorting as needed to emphasize sheets with longer load times.

Save Your Work:

Once the new worksheet and the performance recording are complete, ensure all work is saved.

Navigate to the 'File' menu and click 'Save', confirming that changes are stored in the workbook.

References:

Tableau Help Documentation: Provides guidance on how to start and stop performance recordings and analyze them.

Tableau Visualization Techniques: Offers tips on creating effective bar charts for performance data.

By following these steps, you have successfully recorded and analyzed the performance of the Property Transactions dashboard, providing valuable insights into how each component of the dashboard contributes to the overall load time. This analysis is crucial for optimizing dashboard performance and ensuring efficient data visualization.

Topic 3, Knowledge-Based Section B

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.