Analytics-Con-301 Exam Dumps - Salesforce Consultant Questions and Answers

To compute the required calculations and update the worksheet in Tableau Desktop, follow these steps:

Compute Average Sales by Segment for Each Category and Year:

Open the CC workbook and navigate to the Categorical Sales worksheet.

Drag the 'Sales' field to the Rows shelf if it's not already there.

Drag the 'Segment' field to the Rows shelf as well, placing it next to 'Category' and 'Year'.

Right-click on the 'Sales' field in the Rows shelf and select 'Quick Table Calculation' > 'Average'. This will compute the average sales for each segment within each category and year.

Create a Calculation for Year-over-Year Percentage Change:

Right-click in the data pane and select 'Create Calculated Field'.

Name the calculated field something descriptive, e.g., "YoY Sales Change".

Enter the formula to calculate the year-over-year percentage change:

(ZN(SUM([Sales])) - LOOKUP(ZN(SUM([Sales])), -1)) / ABS(LOOKUP(ZN(SUM([Sales])), -1))

Click 'OK' to save the calculated field.

Replace the Original Measure with the Year-over-Year Percentage Change in the Crosstab:

Remove the original 'Sales' measure from the view by dragging it off the Rows shelf.

Drag the newly created "YoY Sales Change" calculated field to the Rows shelf where the 'Sales' field was originally.

Format the "YoY Sales Change" field to display as a percentage. Right-click on the field in the Rows shelf, select 'Format', and adjust the number format to percentage.

Save Your Changes:

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

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 shape the data in the "US Population Estimates" data source and enter the total number of records into the "Total Records" parameter in Tableau Desktop, 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 Population worksheet by selecting its tab at the bottom of the window.

Format and Shape the Data:

Ensure the data types match those specified in the requirements: Sex, Origin, Race as strings; Year, Age, Population as whole numbers.

To verify or change the data type, click on the dropdown arrow next to each field name in the Data pane and select "Change Data Type" if necessary.

Calculate Total Number of Records:

Create a new calculated field named "Total Records". To do this, right-click in the Data pane and select "Create Calculated Field".

Enter the formula COUNT([Record ID]) or SUM([Number of Records]) depending on how the data source identifies each row uniquely.

Drag this new calculated field onto the worksheet to display the total number of records.

Enter the Value into the Total Records Parameter:

Locate the "Total Records" parameter in the Data pane. Right-click on the parameter and select "Edit".

Manually enter the number displayed from the calculated field into the parameter, ensuring accuracy to meet the data shaping requirement.

Save Your Changes:

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

To modify the Percent Contribution calculated field to use a Level of Detail (LOD) expression and accurately calculate the percentage contribution of each manufacturer to the total quantity, follow these steps:

Open the CC Workbook and Access the Worksheet:

Double-click on the CC workbook from the desktop to open it in Tableau Desktop.

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

Modify the Percent Contribution Calculated Field:

Navigate to the Data pane and find the "Percent Contribution" calculated field.

Right-click on the "Percent Contribution" field and select 'Edit'.

Modify the formula to incorporate an LOD expression that calculates the total quantity across all manufacturers and the specific quantity per manufacturer:

{FIXED [Manufacturer]: SUM([Quantity])} / {SUM([Quantity])}Quantity])}

This formula uses {FIXED [Manufacturer]: SUM([Quantity])} to compute the total quantity contributed by each manufacturer, regardless of other dimensions in the view. The total quantity {SUM([Quantity])} calculates the grand total across all manufacturers. The division calculates the percentage contribution.

Click 'OK' to save the updated calculated field.

Enter Percentage for Newell:

With the updated "Percent Contribution" field, drag it onto the view to update the chart or table.

Identify the value corresponding to 'Newell' in the updated visualization.

Round this value to the nearest hundredth of a percent as required.

Enter this value into the "Newell % Contribution" parameter. To do this, locate the parameter in the Data pane or on the dashboard, right-click it, and choose 'Edit'. Enter the calculated percentage for Newell.

Save Your Changes:

From the File menu, click 'Save' to store all the modifications you have made to the workbook.

To add a line showing the cumulative percentage of sales contributed by each product to the incremental sales in the Incremental worksheet of your Tableau Desktop, follow these detailed 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 Incremental worksheet by clicking on its tab at the bottom of the window.

Calculate Cumulative Sales Percentage:

Create a new calculated field to compute the cumulative percentage of sales. Right-click in the Data pane and select 'Create Calculated Field'.

Name this field "Cumulative Sales Percentage".

Enter the following formula to calculate the running sum of sales as a percentage of the total sales:

(RUNNING_SUM(SUM([Sales])) / TOTAL(SUM([Sales])) [Sales]))

Click 'OK' to save the calculated field.

Add the Cumulative Sales Percentage Line to the Chart:

Drag the "Cumulative Sales Percentage" field to the Rows shelf, placing it next to the existing Sales measure.

Ensure that the cumulative line appears as a continuous line. Right-click on the "Cumulative Sales Percentage" field on the Rows shelf, select 'Change Chart Type', and choose 'Line'.

Adjust the axis to synchronize or dual-axis if necessary. Right-click on the axis of the "Cumulative Sales Percentage" and select 'Synchronize Axis' if it's on a dual-axis setup.

Format the Cumulative Sales Percentage Line:

Click on the "Cumulative Sales Percentage" line in the visualization.

Navigate to the 'Format' pane to adjust the line style, thickness, and color to make it distinct from other data in the chart.

Save Your Changes:

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

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.

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.

Comprehensive and Detailed Explanation From Exact Extract:

View Acceleration is a Tableau Server and Tableau Cloud feature that speeds up slow-loading views by precomputing their queries in the background.

According to Tableau’s server and cloud performance documentation:

When View Acceleration is enabled for a view, Tableau runs the queries behind that view on a background process and stores the results in memory.

When an end user later opens the view, Tableau can serve the precomputed results immediately, rather than running the potentially long-running queries at that moment.

This improves initial load time significantly for views that are slow because of heavy queries.

It does not only work with extract-based data sources (it can also help with many live connections), so option A is too limited.

It does not change the client-side rendering engine, so option C is incorrect.

It is not specific to transient functions but to any view where the query is expensive, so option D is not accurate.

Therefore, the correct description is that View Acceleration precompiles and fetches workbook data in a background process, which matches option B.

Tableau Server and Tableau Cloud help describing View Acceleration as precomputing and caching view results using background processes.

Performance tuning guidance recommending View Acceleration for views with slow query execution.

Comprehensive and Detailed Explanation From Exact Extract:

According to Tableau’s Performance Optimization guidance, rendering time becomes the largest bottleneck when excessive marks, dense data, or overly complex visualizations appear on worksheets. Rendering is the last stage in the Tableau Order of Operations and is directly affected by how many marks must be drawn and how visually complex each view is.

Tableau’s performance recommendations explain:

When a performance recording shows that Rendering is the slowest step, the most effective improvement is to reduce the number of marks (records) in the view.

Rendering time is determined by the number of marks, shapes, headers, labels, and visual elements Tableau must draw.

Reducing the amount of data displayed on each worksheet is the most impactful change when rendering is the dominant delay.

Option B directly aligns with this: updating worksheets to reduce the number of records displayed lowers the number of marks, reduces visual density, and improves rendering speed.

Option A is not effective because changing dashboard size does not reduce the number of marks.

Option C would degrade performance because live connections are typically slower than extracts.

Option D improves data preparation and may reduce extract load times, but it does not directly address rendering unless the unused data was contributing to marks in the view. The question indicates the bottleneck is specifically rendering, so reducing marks is the most appropriate action.

Therefore, the most effective solution to reduce rendering time is to reduce the number of records (marks) displayed on worksheets.

Tableau Performance Recording guidance describing rendering as the slowest stage when too many marks are present.

Tableau Performance Checklist recommending reducing the number of marks in views to improve rendering.

Tableau Desktop help sections on best practices for improving visualization performance when rendering dominates.

Comprehensive and Detailed Explanation From Exact Extract:

When Tableau Data Management is enabled, Tableau Catalog provides Lineage capabilities that map connections between:

External databases

Tables

Data sources

Workbooks

Fields

Tableau documentation states that the Lineage tab for any external asset (such as a database or table):

Shows all connected workbooks

Shows dependencies and impact analysis

Allows admins to instantly assess how many analytics assets will be affected by a data warehouse migration

Option A directly uses Tableau Catalog to perform exactly this task.

Option B is unnecessary because the Catalog lineage tool already provides this information without development effort.

Option C is completely inappropriate because it offers no analysis or planning.

Option D is too time-consuming and unnecessary, especially when Tableau Catalog provides an automated dependency map.

Therefore, the correct method is to use the Lineage tab in External Assets.

Tableau Catalog lineage documentation showing how to view impacted workbooks.

External Assets and data source dependency features in Tableau Data Management.

Impact analysis best practices for data warehouse migration using Tableau Catalog.