Analytics-Con-301 Questions Prepare with Learning Information! 2026 Regularly updated [Q44-Q63]

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Analytics-Con-301 Questions Prepare with Learning Information! 2026 Regularly updated

Get Analytics-Con-301 Products Practice Material for Analytics-Con-301 Exam Question Preparation

Salesforce Analytics-Con-301 Exam Syllabus Topics:

Topic	Details
Topic 1	Data Analysis: This domain targets Tableau Consultants to plan and prepare data connections effectively. It includes recommending data transformation strategies, designing row-level security (RLS) data structures, and implementing advanced data connections such as Web Data Connectors and Tableau Bridge. Skills in specifying granularity and aggregation strategies for data sources across Tableau products are emphasized.
Topic 2	Data Management: This part focuses on establishing governance and support for published content. Tableau Consultants are expected to manage data security, publish and maintain data sources and workbooks, and oversee content access. It includes applying governance best practices, using metadata APIs, and supporting administration functions to maintain data integrity and accessibility.
Topic 3	Business Consulting: For Tableau Consultants, this section involves designing and troubleshooting calculations and workbooks to meet advanced analytical use cases. It covers selecting appropriate chart types, applying Tableau’s order of operations in calculations, building interactivity into dashboards, and optimizing workbook performance by resolving resource-intensive queries and other design-related issues.

Q44. A client currently has a workbook with the table shown below.

Which method will produce the output for the Total Sales Value field for all the categories shown in the table?

Quick Table Calculation

A Window Function

Level of Detail (LOD) Calculation

MAX() Function

Q45. A Tableau consultant tasked with evaluating a data structure is handed the below sample dataset.
Which two statements are true about the dataset? Choose two.

The data structure will require a lot of maintenance, as maintenance will need to be done to handle a new column for a new year.

The names of the columns are accurate and indicate what the data values actually mean.

The data can be pivoted in order to enable a year selector.

The data needs to be denormalized before it can be used.

Q46. A consultant creates a histogram that presents the distribution of profits across a client’s customers. The labels on the bars show percent shares. The consultant used a quick table calculation to create the labels.
Now, the client wants to limit the view to the bins that have at least a 15% share. The consultant creates a profit filter but it changes the percent labels.
Which approach should the consultant use to produce the desired result?

Use a calculation with TOTAL() function instead of a quick table calculation.

Add the [Profit] filter to the context.

Filter with a table calculation WINDOW_AVG(MIN([Profit]), first(), last())

Filter with the table calculation used to create labels.

When a filter is applied directly to the view, it can affect the calculation of percentages in a histogram because it changes the underlying data that the quick table calculation is based on. To avoid this, adding the [Profit] filter to the context will maintain the original calculation of percent shares while filtering out bins with less than a 15% share. This is because context filters are applied before any other calculations, so the percent shares calculated will be based on the context-filtered data, thus preserving the integrity of the original percent labels.
References: The solution is based on the principles of context filters and their order of operations in Tableau, which are documented in Tableau’s official resources and community discussions123.
When a histogram is created showing the distribution of profits with labels indicating percent shares using a quick table calculation, and a need arises to limit the view to bins with at least a 15% share, applying a standard profit filter directly may undesirably alter how the percent labels calculate because they depend on the overall distribution of data. Placing the [Profit] filter into the context makes it a “context filter,” which effectively changes how data is filtered in calculations:
Create a Context Filter: Right-click on the profit filter and select “Add to Context”. This action changes the order of operations in filtering, meaning the context filter is applied first.
Adjust the Percent Calculation: With the profit filter set in the context, it first reduces the data set to only those profits that meet the filter criteria. Subsequently, any table calculations (like the percent share labels) are computed based on this reduced data set.
View Update: The view now updates to display only those bins where the profits are at least 15%, and the percent share labels recalculated to reflect the distribution of only the filtered (contextual) data.
References:
Context Filters in Tableau: Context filters are used to filter the data passed down to other filters, calculations, the marks card, and the view. By setting the profit filter as a context filter, it ensures that calculations such as the percentage shares are based only on the filtered subset of the data.

Q47. From the desktop, open the CC workbook.
Open the Incremental worksheet.
You need to add a line to the chart that
shows the cumulative percentage of sales
contributed by each product to the
incremental sales.
From the File menu in Tableau Desktop, click
Save.

Q48. A Tableau Server customer is interested in measuring content and platform usage. Which two features should the consultant use? Choose two.

Tableau Pulse

Tableau Server repository

Admin Insights page

Server Status page

Q49. A client wants to see data for only the last day in a dataset and the last day is always yesterday. The date is represented with the field Ship Date.
The client is not concerned about the daily refresh results. The volume of data is so large that performance is their priority. In the future, the client will be able to move the calculation to the underlying database, but not at this time.
The solution should offer the best performance.
Which approach should the consultant use to produce the desired results?

Filter MONTH/DAY/YEAR on [Ship Date] field and use an option to filter to the latest date value when the workbook opens.

Filter on calculation [Ship Date]=TODAY()-1.

Filter on Ship Date field using the Yesterday option.

Filter on calculation [Ship Date]={MAX([Ship Date])}.

Q50. A worksheet uses a LOOKUP function to display Sales by Month, Year of Order Date, and sales from the last
12 months. A consultant wants to use a Relative Date Filter to filter for data from the last 12 months.
However, when the consultant does this, the prior year’s data is removed from the sheet.
Which two actions should the consultant take to retain the prior year’s data after applying the filter? Choose two.

Replace the LOOKUP function with a FIXED Level of Detail (LOD) expression.

Set the Relative Date filter as a Context Filter instead of Measure Filter.

Create the following calculation: LOOKUP(MIN([Order Date]),0). Filter on that calculation instead of Order Date.

Create the following calculation: DATEDIFF(‘month’, [Order Date], {MAX([Order Date])}) < 12. Hide all False values.

Comprehensive and Detailed Explanation From Exact Extract:
A LOOKUP table calculation requires access to rows outside the filtered date range so that the calculation can reference prior data. When a Relative Date Filter removes older data before the table calculation is evaluated, the LOOKUP loses the needed rows, causing the prior year’s data to disappear.
Tableau’s order of operations states:
* Relative Date Filters act early (at the dimension filter stage).
* Table calculations act very late.
* To preserve table calculation context, filters must not remove necessary rows.
Two Tableau-documented approaches address this:
Explanation for B
Setting the Relative Date Filter as a Context Filter allows table calculations to operate on the full dataset needed for LOOKUP. Context filters create a separate temporary table, and subsequent filters like table calculations evaluate after the context is established.
This ensures older rows are still available to the LOOKUP function.
Explanation for C
Creating a field such as:
LOOKUP(MIN([Order Date]), 0)
and filtering on this field instead of Order Date converts the filter into a table calculation filter, which occurs after the LOOKUP computation. Tableau documentation explains that table calculation filters preserve the full dataset required for the LOOKUP window.
This ensures that the LOOKUP still has access to last year’s values even when filtering for the current 12 months.
Why A is incorrect
Replacing LOOKUP with an LOD changes the logic entirely.
LOD expressions cannot replicate moving-window or lag-type behavior.
Why D is incorrect
DATEDIFF logic can replicate a rolling window, but hiding False values is essentially a manual filter and does not preserve the integrity of the LOOKUP’s required partitioning. It also contradicts Tableau’s recommended approach for maintaining table calculation context.
* Tableau Order of Operations explaining why table calculation filters preserve data for LOOKUP.
* Tableau documentation on context filters and how they allow more data to remain available for downstream table calculations.
* Tableau guidance on how Relative Date Filters interact with table calculations.
* Best practices for preserving table calculation window rows when filtering.

Q51. A client wants to produce a visualization to show quarterly profit growth and aggregated sales totals across a number of product categories from the data provided below.

Which set of charts should the consultant use to meet the client’s requirements?

Line and bubble charts

Waterfall chart and tree map

Gantt and bar charts

Scatter plot and pie chart

Q52. A company’s Tableau Cloud admin wants to maintain control over what content gets published to its site for viewers, while also supporting self-service for dashboard creators.
Which governance strategy should the admin implement?

Create sandbox projects to contain ad hoc content and production projects for validated content.

Maintain a separate sandbox site and use the Content Migration Tool to promote content between sites.

Allow dashboard creators to publish to their Personal Space and for site administrators to move content to projects.

Restrict users’ permission to view data sources used in uncertified dashboards.

Q53. A client has a database that stores widget inventory by day and it is updated on a nonstandard schedule as shown below.

They want a data visualization that shows widget inventory daily, however their business unit does not have the ability to modify the data warehouse structure.
What should the client do to achieve the desired result?

Create a temporary table in the database.

Use Tableau Desktop to visualize null values.

Update the Widget Inventory Table to be a daily snapshot.

Use Tableau Prep to add new rows.

Q54. A client requests a published Tableau data source that is connected to SQL Server. The client needs to leverage the multiple tables option to create an extract. The extract will include partial data from the SQL Server data source.
Which action will reduce the amount of data in the extract?

Use an extract filter.

Aggregate the extract to the visible dimensions.

Define the filters by using custom SQL.

Set up the extract as an incremental refresh.

Q55. Sales managers use a daily extract from Snowflake to see the previous day’s snapshot.
Sales managers should only see statistics for their direct reports.
The company has Tableau Data Management on Tableau Cloud.
A consultant must design a centralized, low-maintenance RLS strategy.
What should the consultant implement?

Built-in RLS security in Snowflake

Data policy

Manual user filter

Dynamic user filter

Q56. A stakeholder has multiple files saved (CSV/Tables) in a single location. A few files from the location are required for analysis. Data transformation (calculations) is required for the files before designing the visuals. The files have the following attributes:
. All files have the same schema.
. Multiple files have something in common among their file names.
. Each file has a unique key column.
Which data transformation strategy should the consultant use to deliver the best optimized result?

Use join option to combine/merge all the files together before doing the data transformation (calculations).

Use wildcard Union option to combine/merge all the files together before doing the data transformation (calculations).

Apply the data transformation (calculations) in each require file and do the wildcard union to combine
/merge before designing the visuals.

Apply the data transformation (calculations) in each require file and do the join to combine/merge before designing the visuals.

Q57. A client wants to report Saturday and Sunday regardless of the workbook’s data source’s locale settings.
Which calculation should the consultant recommend?

DATEPART(‘weekday’, [Order Date])>=6

DATEPART(‘iso-weekday’, [Order Date])>=6

DATENAME(‘iso-weekday’, [Order Date])>=6

DATEPART(‘iso-weekday’, [Order Date])=1 or DATEPART(‘iso-weekday’, [Order Date])=7

Q58. A new Tableau user created a simple dashboard on Tableau Server using supply chain data. Now, the user wants to know if they created the dashboard in accordance with specific performance best practices.
Which approach should the consultant recommend for the client to make this determination?

Use inbuilt dashboards in Tableau Server to troubleshoot the performance.

Use Performance Recording on Tableau Server.

Use Performance Recording in Tableau Desktop.

Run Workbook Optimizer.

Q59. A client wants to flag orders that have sales higher than the regional average.
Which calculated field will produce the required result?

[Sales]
>
{ FIXED [Order ID] : SUM([Sales]) }

{ FIXED [Order ID] : SUM([Sales]) }
>
{ FIXED [Region] : SUM([Sales]) }

{ FIXED [Order ID] : SUM([Sales]) }
>
{ FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }

{ FIXED [Order ID] : SUM([Sales]) }
>
{ INCLUDE [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }

Q60. A company has a data source for sales transactions. The data source has the following characteristics:
. Millions of transactions occur weekly.
. The transactions are added nightly.
. Incorrect transactions are revised every week on Saturday.
* The end users need to see up-to-date data daily.
A consultant needs to publish a data source in Tableau Server to ensure that all the transactions in the data source are available.
What should the consultant do to create and publish the data?

Publish an incremental extract refresh every day and perform a full extract refresh every Saturday.

Publish a live connection to Tableau Server.

Publish an incremental refresh every Saturday.

Publish an incremental extract refresh every day and publish a secondary data set containing data revisions.

Q61. SIMULATION
From the desktop, open the CC workbook.
Open the Manufacturers worksheet.
The Manufacturers worksheet is used to
analyze the quantity of items contributed by
each manufacturer.
You need to modify the Percent
Contribution calculated field to use a Level
of Detail (LOD) expression that calculates
the percentage contribution of each
manufacturer to the total quantity.
Enter the percentage for Newell to the
nearest hundredth of a percent into the
Newell % Contribution parameter.
From the File menu in Tableau Desktop, click
Save.

See the complete Steps below in Explanation
Explanation:
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.
References:
Tableau Help: Offers detailed guidance on using LOD expressions for precise and context-independent aggregations.
Tableau Desktop User Guide: Provides comprehensive instructions on managing calculated fields and parameters, ensuring accurate data analysis.
By following these steps, you will have successfully updated the calculation for percent contribution using LOD expressions, providing a more accurate analysis of each manufacturer’s contribution to the total quantity. Moreover, updating the parameter with Newell’s specific contribution rounds out the task by reflecting precise data inputs for reporting or further analysis.

Q62. From the desktop, open the CC workbook. Use the US Population Estimates data source.
You need to shape the data in US Population Estimates by using Tableau Desktop. The data must be formatted as shown in the following table.

Open the Population worksheet. Enter the total number of records contained in the data set into the Total Records parameter.
From the File menu in Tableau Desktop, click Save.

See the complete Steps below in Explanation:
Explanation:
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.
References:
Tableau Desktop Guide: Provides detailed instructions on managing data types, creating calculated fields, and updating parameters.
Tableau Data Shaping Techniques: Outlines effective methods for manipulating and structuring data for analysis.
This process will ensure the data in the “US Population Estimates” is accurately shaped according to the specified format and that the total number of records is correctly calculated and entered into the designated parameter. This thorough approach ensures data integrity and accuracy in reporting.

Q63. A consultant used Tableau Data Catalog to determine which workbooks will be affected by a field change.
Catalog shows:
* Published Data Source # 7 connected workbooks
* Field search (Lineage tab) # 6 impacted workbooks
The client asks: Why 7 connected, but only 6 impacted?

The field is used twice in a single workbook.

The consultant lacked sufficient permissions to see the seventh workbook.

The field being altered is not used in the seventh workbook.

The seventh workbook is connected via Custom SQL so it didn’t appear in the list.