Free Practice Questions for the Salesforce Tableau Data Analyst Analytics-DA-201 Exam (2026 Updated)

To ensure that users can see other published dashboards from their current dashboard when publishing a workbook to Tableau Server, you need to enable the option that shows sheets as tabs. This allows users to navigate between different sheets (dashboards) within the published workbook.

In the provided Publish Workbook to Tableau Server dialog box, you should check the option labeled:

" Show sheets as tabs "

This setting will display the sheets as tabs on Tableau Server, enabling users to switch between dashboards easily.

https://help.tableau.com/current/pro/desktop/en-us/parameters_swap.htm

This formula uses a parameter (Pick Measure) to switch between the Sales and Profit measures. When the user selects ' 1 ' , it shows Sales, and when ' 2 ' is selected, it shows Profit. This dynamic switching is enabled by the Case function.

To configure the shapes to be much larger than the line, you need to duplicate Population and drag it to the second Marks card. This will create a dual axis chart with two measures on one axis. You can then select Shape on one Marks card and Line on another Marks card, and adjust the size of each mark independently using the Size slider or menu. References: https://help.tableau.com/current/pro/desktop/en-us/multiplemeasures_dualaxes.htm https://help.tableau.com/current/pro/desktop/en-us/marks_markproperties_size.htm

In a dual-axis chart in Tableau, if you want to have two different visual mark types (like a shape and a line) and configure them differently (such as making one larger than the other), you would need to duplicate the measure. You then drag this duplicate to the second Marks card (which represents the second axis). There, you can adjust the size of the marks (shapes, in this case) independently of the line marks on the first Marks card.

To share a dashboard that contains confidential information about patients health and needs to always be up to date for a team of healthcare workers, you should publish it to Tableau Server. This will allow you to control who can access and interact with your dashboard, as well as schedule automatic refreshes of your data source or extract. Publishing to Tableau Public would expose your data to anyone on the internet, printing to PDF would not update your data, and exporting as a .twbx would require sending a large file that might not be compatible with other versions of Tableau. References: https://help.tableau.com/current/pro/desktop/en-us/publish_workbooks_share.htm https://help.tableau.com/current/pro/desktop/en-us/publish_workbooks_tableauserver.htm

When sharing sensitive and confidential information that needs to be kept up-to-date, such as patient health data for a team of healthcare workers, the best practice is to publish the dashboard to Tableau Server. Tableau Server is designed for secure, controlled access and can be configured to ensure that data is refreshed as needed. Publishing to Tableau Public is not secure for confidential data, printing to PDF or exporting as a .twbx does not allow for live data updates.

The LAST() function in Tableau returns the number of rows from the current row to the last row in the partition. When you compute using ' Order Date ' , it will change the partitioning of the calculation. If ' Consumer ' in ' 2018 ' is the last row in its partition when computed by ' Order Date ' , then LAST() will return 0 for that cell.

The LAST() function in Tableau is a table calculation that returns the number of rows from the current row to the last row in the partition. The value of LAST() is 0 for the last row, increases by 1 for each row above the last row, and can be negative for rows below the current row if there are such rows in the partition.

In the provided visualization, LAST() is set to compute using Table (across). Changing the compute mode to use " Order Date " will adjust the partitioning of the data upon which the LAST() function is calculated. Since " Order Date " is likely to be a unique value per row (assuming each order has a unique date), each row becomes its own partition.

For the Consumer segment of the year 2018, if " Order Date " is unique for each row, then the last row in each partition (in this case, each individual row) will have a LAST() value of 0 because there are no other rows in the partition - it ' s the last row of its own partition.

Therefore, when you change the compute mode of LAST() to use " Order Date " , each cell under the Consumer segment for the year 2018 will have the LAST() value of 0, because each order date creates a partition of one, making every row the last in its partition.

To calculate the ranking shown in the Rank field, you need to use the RANK_UNIQUE function, which returns the unique rank of each value in a partition. You need to specify the expression as SUM([Sales]), which calculates the total sales for each product. You also need to specify the order as descending, which means that the highest sales will have the lowest rank. Finally, you need to specify the restart as every [Category] , which means that the ranking will reset for each category. References: https://help.tableau.com/current/pro/desktop/en-us/functions_functions_tablecalculation.htm https://help.tableau.com/current/pro/desktop/en-us/calculations_calculatedfields_lod_rank.htm

FIXED is the Level of Detail scoping keyword designed to compute an aggregation using explicitly specified dimensions without reference to the dimensions currently present in the view. For regional totals, an expression such as {FIXED [Region] : SUM([Sales] )} calculates sales at the Region level even when the visualization includes additional dimensions such as State or Customer. INCLUDE adds a dimension to the view’s level of detail, while EXCLUDE removes specified view dimensions; both therefore depend on the view context. SUM by itself is a standard aggregate and operates at the current visualization level of detail. Because the requirement states that total regional sales must be calculated regardless of what is in the view, FIXED provides the necessary view-independent level of detail.

A dynamic Top 10 requirement should be implemented with a dynamic set, not with a manual selection or static group. The analyst can create a set on the Year dimension, configure its Top tab to retain the top 10 members according to the relevant medal-count measure, and then place the resulting IN/OUT set on Color on the Marks card. Tableau recalculates the set as the underlying data or ranking changes, so whichever ten years currently meet the Top 10 condition receive one color and the remaining values receive another. Manually selecting ten bars or manually creating a set from currently selected bars produces a fixed membership. A group is also static unless manually changed. Tableau’s Top N guidance demonstrates dragging a Top N set to Color to distinguish the dynamic subset.

Tableau relationships provide a logical-layer approach to combining tables without requiring a fixed join type when the data source is created. The related tables remain separate, preserving their native level of detail. When a visualization is queried, Tableau evaluates the fields currently being used and automatically determines the appropriate joins required for that analytical context. This makes relationships dynamic and context-aware. Option A is incorrect because the matching fields that define the relationship are established when the relationship is configured; they do not change simply because of user interactions. Option B is incorrect because relationships do not store the entire data source in a pre-aggregated format. Option D describes physical joining more closely because relationships specifically avoid merging all related tables into one physical table. Therefore, C accurately describes the principal advantage.

To organize the tables in the Data pane based on the type of data contained within the tables, you should use folders. Folders are a way to manually group fields, parameters, sets, or tables in the Data pane according to your preference. You can create folders by right-clicking on the fields or tables you want to group and selecting Folders > Create Folder. You can also drag and drop fields or tables into existing folders. You can name the folders according to the type of data they contain, such as sales, customer, product, etc. Folders can help you find and access the fields or tables you need more easily and efficiently. References:

Organize and Customize Fields in the Data Pane - Tableau

Tableau Certified Data Analyst Study Guide

When you sign in to a Tableau Server site from Tableau Desktop and search for a published data source, you will see all the data sources published to the site within the folders to which you have access. You will not see data sources published to other sites or folders that you do not have permission to view. You can also filter your search by project, owner, or tag. References: https://help.tableau.com/current/pro/desktop/en-us/connect_basic.htm https://help.tableau.com/current/pro/desktop/en-us/connect_tableauserver.htm

When signed in to Tableau Server from Tableau Desktop, you ' ll only be able to see the data sources that have been published to the site and are within the folders that you have been granted access to. Tableau ' s permission and project structure mean that you won ' t see all data sources from the entire server unless you have permissions to do so.

B is the verified answer; the selection shown in the candidate PDF is not reliable here. The difficulty is that FullName contains a variable number of space delimiters. A simple “split all” operation would produce First | Last for a two-part name but First | Middle | Last for a three-part name, so the second result column does not consistently represent the middle name. Tableau’s Custom Split functionality allows splitting from the first or last occurrences of a delimiter. The analyst can therefore reliably extract the first and last names regardless of whether a middle name exists, and derive the middle component when present. Tableau’s documentation notes that Custom Split provides control over first N, last N, or all occurrences and is useful when separator counts vary between records.

To configure the dashboard to ensure that selecting a data point on the map only filters the Detail table, you should select Ignore Actions from the context menu of Sales over time. Ignore Actions is a feature that allows you to exclude a sheet from being affected by any actions on the dashboard, such as filters or highlights. You can select Ignore Actions by right-clicking on a sheet on the dashboard and selecting Ignore Actions from the menu.

In this case, you want to exclude Sales over time from being filtered by the map, so you should select Ignore Actions from its context menu. This will make Sales over time ignore any selections on the map and show all values. The Detail table will still be filtered by the map as usual.

The other options are not correct for this scenario. Removing Dashboard Item will delete Sales over time from the dashboard, which is not what you want. Deselecting Use as Filter will disable the map as a filter for any sheet on the dashboard, which is not what you want. Selecting Deselect will clear any selections on the map, but it will not prevent Sales over time from being filtered by future selections. References: https://help.tableau.com/current/pro/desktop/en-us/actions.htm https://help.tableau.com/current/pro/desktop/en-us/actions_ignore.htm

On a Tableau dashboard, when a map is used as a filter, it affects all other sheets in the dashboard by default. To restrict the filter action to only affect the Detail table and not the ' Sales over time ' chart, you would modify the action settings. By selecting " Ignore Actions " from the context menu of the ' Sales over time ' chart, it will no longer respond to the filtering action initiated by selecting data points on the map.

To apply a custom data role to a field, you need to select the data type of the field and then choose the data role from the list of available roles. This will validate the values in the field against the data role and mark any invalid values with a red exclamation mark. To fix the invalid values, you can use the Group Values option and select the Spelling algorithm, which will group values that are close in spelling and replace them with the most frequent value in the group. This will help you standardize the values in the Material field and match them with the Role1 data role. References: The information is based on the following sources:

Use Data Roles to Validate your Data - Tableau

New in Tableau Prep: Automatically identify data quality issues with Data Roles

To determine the Rank Score value for Student ID 4220, we look at the visualization provided and apply the table calculation of RANK(AVG([Score])) . This function will rank the average scores in ascending order by default, with the lowest score receiving the rank of 1.

Based on the provided visualization, the scores for the students are as follows (from lowest to highest average score):

Student ID 4183: 39 (Rank 1)

Student ID 4220: 71 (Rank 6)

Student ID 4247: 71 (Rank 6, same score as ID 4220 so they share the same rank)

Student ID 4124: 75.5

Student ID 4050: 64

Student ID 4205: 67

Student ID 4056: 66

Since Student ID 4220 has an average score of 71, which is the third-highest score, it shares the rank with Student ID 4247. However, since Tableau ranks without gaps, the actual rank assigned is 6, considering that there are two students with a rank of 4 (due to the same average score being the second lowest), making the next rank number 6.

Note: The actual ranks for the highest scores are not provided, but they are not needed to determine the rank for Student ID 4220.

https://help.tableau.com/current/prep/en-us/prep_calculations.htm

A reusable custom color palette is defined through Tableau’s preferences configuration rather than by formatting a single worksheet. The Preferences.tps file resides in My Tableau Repository and uses XML tags to define named color palettes and their color values. After the palette is added and Tableau Desktop is restarted, the palette becomes available from the color-palette selector and can be used across workbooks, which matches the branding requirement. Custom shapes are unrelated because they control mark appearance rather than color definitions. Worksheet shading affects only formatting in a particular workbook or sheet, and the standard color picker does not create the same reusable named palette in the manner described by this question. Therefore, modifying the XML in Preferences.tps is the correct exam-aligned method.

The required logic must first evaluate the activity history independently for each Call ID, which is why a FIXED LOD expression is appropriate. {FIXED [Call ID] : ...} establishes Call ID as the calculation grain regardless of the visualization’s dimensions. Within each call, [Activity Name] = " Assign Technician " produces a Boolean condition. Applying MAX to that condition determines whether an assignment activity exists for that call. If one exists, the calculation returns 0; otherwise it returns 1. The outer SUM then totals the calls that never received an assignment. INCLUDE does not provide the required fixed call-level evaluation, while the other expressions either count activity records rather than calls or do not form valid LOD logic for the requirement. Therefore, A is correct.

To combine the two tables that contain data about books in a library and ensure that all the data is retained, you should use a full outer join. A full outer join is a type of join that returns all rows from both tables, regardless of whether there is a match or not. If there is no match, null values are filled in for the missing fields.

To perform a full outer join, you need to do the following steps:

Connect to both tables as your data sources in Tableau. You can use either live or extract connections.

Drag one table to the canvas and drop it on top of another table. This will create a join between them based on a common field.

Click on the join icon between the tables and select Full Outer Join from the drop-down list. This will change the join type to full outer join and show all rows from both tables.

Optionally, you can add or remove join clauses by clicking on Add or Remove buttons next to each clause. You can also change or rename fields by clicking on them.

The other types of joins are not correct for this scenario. An inner join returns only the rows that have a match in both tables, which will exclude any books that are missing from either table. A left join returns all rows from the left table and only the matching rows from the right table, which will exclude any books that are only in the right table. A right join returns all rows from the right table and only the matching rows from the left table, which will exclude any books that are only in the left table. References: https://help.tableau.com/current/pro/desktop/en-us/joining_tables.htm https://help.tableau.com/current/pro/desktop/en-us/join_types.htm

When combining two datasets that are both incomplete and where it ' s important to retain all data from both sources, a full outer join is appropriate. This type of join ensures that all records from both tables are included in the combined dataset, even if there are no matching records in the other table.

To calculate the month to date value of the prior year, you need to filter the order date to be between the first day of the same month of the previous year and the same day of the previous year. You can use the calculated fields [Calc1] and [Calc2] to get these dates. [Calc1] returns the date that is one year before today, and [Calc2] returns the date that is the first day of the month of [Calc1]. By using these fields in the filter condition, you can get the desired result.

To minimize the whitespace between the sheets, you should configure the padding of the sheets and the dashboard. Padding is the amount of space between the edge of a sheet or dashboard and its content. You can adjust the padding by using the Layout tab in the Format pane. You can reduce the padding for each sheet by selecting the sheet and changing the values for the inner and outer padding. You can also reduce the padding for the dashboard by selecting the dashboard and changing the values for the outer padding. Reducing the padding will make the sheets and the dashboard more compact and eliminate unnecessary whitespace. References:

Format Dashboards - Tableau

Tableau Certified Data Analyst Study Guide

To ensure that the data is updated every hour, you need to select Extract Refreshes from the data source menu on Tableau Server. This will allow you to add a new extract refresh schedule or edit an existing one. You can specify the frequency and time of the refresh, as well as any custom options or credentials. New will create a new data source, Connected Workbooks will show you which workbooks use this data source, and Connections will show you which tables or files are connected to this data source. References: https://help.tableau.com/current/server/en-us/refresh_extracts.htm https://help.tableau.com/current/server/en-us/refresh_extracts_add.htm

To ensure that the data is updated every hour on Tableau Server, you would need to go to the " Extract Refreshes " option. Here, you can schedule the data extracts to refresh at the desired frequency, which in this case would be every hour.

A Running Total accumulates the measure sequentially across the addressing dimension. With Year on Columns and SUM(Downloads) in the view, Tableau starts with the first year ' s downloads and progressively adds each subsequent year ' s value to the accumulated total. The resulting bars therefore represent all downloads received up to each year since release rather than the downloads for that individual year alone. YTD Total is intended for accumulation within a calendar year and commonly restarts with the new year. Percent of Total expresses each value as a proportion of the full partition, while Year Over Year Growth compares the relative change between consecutive annual values. Tableau lists Running Total as a standard quick table calculation specifically for cumulative analysis. Therefore, B is the appropriate calculation.

To combine the tables and meet the requirements, you should use a left join. A left join will keep all the records from the left table (Employeelnfo) and match them with the records from the right table (DepartmentInfo) based on the common field (Department ID). If there is no matching record in the right table, the fields from the right table will be null. This way, you will retain all the records from Employeelnfo, and also include the Department Name, Size, and VP fields from DepartmentInfo. Every record will have a full name because it is a field from the left table. A left join will look like this:

The Item hierarchy separates the top-level floating objects from the objects nested under the Tiled section. In the exhibit, Show/Hide, Filters Container, and Legend appear at the top level before the Tiled branch. Total Sales and Horizontal Container are nested inside vertical containers under Tiled, so they belong to the tiled layout structure. Tableau distinguishes tiled items, which participate in a non-overlapping layout grid, from floating items, which can be positioned and layered independently. In Tableau Desktop, floating objects appear at the top level of the Item hierarchy and can be reordered to control their layering. Reading the hierarchy therefore identifies B, D, and E as floating, while A and C are contained within the tiled hierarchy and are not floating objects.

Common Characters: Find and group values that have letters or numbers in common. This option uses the ngram fingerprint algorithm that indexes words by their unique characters after removing punctuation, duplicates, and whitespace. This algorithm works for any supported language. This option isn ' t available for data roles. For example, this algorithm would match names that are represented as " John Smith " and " Smith, John " because they both generate the key " hijmnost " . Since this algorithm doesn ' t consider pronunciation, the value " Tom Jhinois " would have the same key " hijmnost " and would also be included in the group.

Extensions in Tableau are web-based programs that can interact with dashboards. To add a button that allows users to export the dashboard as an image, you would use an Extension object. This could be a custom extension designed to trigger the download of the dashboard view as an image.

An INCLUDE LOD expression is specifically useful when a calculation must incorporate a finer-grained dimension that is not already present in the visualization. INCLUDE adds the specified dimension to the level of detail established by the dimensions currently in the view, calculates the expression at that finer grain, and then allows Tableau to reaggregate the result at the view’s level. For example, { INCLUDE [Customer Name] : SUM([Sales] ) } can calculate sales per customer even when Customer Name itself is absent from the displayed view. If the dimension is already present in the view, INCLUDE generally adds no additional granularity for that field. The dimension does not specifically need to reside on the Marks card, Rows/Columns shelves, or Filters shelf. Therefore, Not in the View is the correct answer.

The current view contains only one aggregated Discount mark for each Vendor, so Tableau does not have enough individual marks within each vendor partition to calculate a meaningful distribution. Adding Invoice Number to Detail increases the level of detail so that each invoice contributes an individual Discount mark while Vendor remains the grouping dimension. Tableau can then calculate quartiles, median, whiskers, and outliers from the underlying distribution. Tableau’s box-plot guidance lists a dimension on Detail as one of the fundamental building blocks of a box-and-whisker plot. Changing the whisker configuration would affect how an already valid distribution is displayed but would not create the missing observations. Count Distinct and converting Discount to discrete would alter the analytical meaning rather than establish the correct mark granularity. Therefore, B is correct.

To change the story point format to show the current story point number out of the total number of story points, you should use the Numbers option in the Layout tab. This option will display the story points as numbers in a horizontal or vertical sequence, such as 1/2, 2/2. You can also choose to show or hide the next and previous arrows for navigation. The Numbers option will help you indicate the progress and order of your story points more clearly than the other options. References:

Creating a Story - Tableau

New in 9.0: Formatting the Story Points Navigator - Tableau

Tableau Certified Data Analyst Study Guide

Option D is the only series whose functions can all operate as string-oriented functions in Tableau. CONTAINS evaluates whether one string contains another substring, and LEN returns the number of characters in a string. MIN can also be applied to string values; for strings, Tableau returns the value that comes first according to the applicable alphabetical or database sort order. The other choices mix string functions with functions from different categories. CEILING is numeric and COUNT is an aggregate; FIRST and LAST are table-calculation functions; DATEADD and NOW are date functions. Although MIN is also documented as an aggregate or comparison function, Tableau’s function reference explicitly supports string arguments for MIN. Therefore, MIN, CONTAINS, and LEN is the valid series.

To add a column that shows the day of the week for each row, you should complete the formula as follows:

DATENAME

(

‘weekday’

, [Order Date])

 The DATENAME function in Tableau returns the name of a specified part of a date or datetime value, such as the year, month, or day. It takes two arguments: the date part and the date. In this question, you want to return the name of the weekday, such as Monday, Tuesday, or Wednesday, for each order date. Therefore, you need to use ‘weekday’ as the date part and [Order Date] as the date. The formula will return a string value that represents the name of the weekday for each order date.

To show the corresponding region when users hover their mouse over any of the bars, you need to drag Region to Tooltip on the Marks card. This will add Region as a field in the tooltip text that appears when users hover over a mark. You can also customize the tooltip text by editing it in the Tooltip dialog box. References: https://help.tableau.com/current/pro/desktop/en- us/buildmanual_shelves.htm https://help.tableau.com/current/pro/desktop/en-us/formatting_tooltips.htm

To show additional information such as the corresponding region when hovering over a bar in Tableau, you can drag the ' Region ' field to the ' Tooltip ' shelf on the ' Marks ' card. This will ensure that when a user hovers over a bar representing a city, the tooltip will dynamically display the region associated with that city.

To add a comment to March 2020 on a line chart, you need to annotate that mark. You can right-click on the mark and select Annotate > Mark from the menu. This will open a dialog box where you can type your comment and format it as you like. You can also drag and drop the annotation to position it on the worksheet. Dragging the growth rate to Text on the Marks card will add a label to every mark on the line chart, enabling captions will show a description of the worksheet at the bottom, and adding a tooltip will show a text box when users hover over a mark. References: https://help.tableau.com/current/pro/desktop/en-us/formatting_annotations.htm https://help.tableau.com/current/pro/desktop/en-us/formatting_annotations_create.htm

To add a comment to a specific point on a line chart, such as March 2020 in the provided visualization, you would use the ' Annotate ' feature. Right-clicking on the data point for March 2020 and selecting ' Annotate ' allows you to add a text annotation directly to the chart, which can be used to highlight and comment on that particular data point.

Data interpreter is a feature that helps you clean and structure your data in Excel before importing it into Tableau. It detects and removes any headers, footers, subtotals, or other elements that are not part of the actual data. It also splits any merged cells and fills in any missing values. In this case, data interpreter provides the following results:

It removes the first three rows and the last two rows that contain headers and footers.

It splits the merged cells in column A and fills in the missing values with “Fiction” or “Non-Fiction”.

It does not remove or change any other rows or cells.

Therefore, the number of rows of data that will be ingested into Tableau as values is 17, which is the number of rows left after removing the headers and footers. References: https://help.tableau.com/current/pro/desktop/en-us/importing_cleaning_up_data.htm https://help.tableau.com/current/pro/desktop/en-us/importing_data_interpreter.htm

Based on the Data Interpreter ' s results and the provided Excel dataset screenshot, the number of rows of data that will be ingested into Tableau as values is 17. The Data Interpreter has identified and excluded headers and footers, and the rows with actual data are considered for analysis.

To have each record alternate between grey and white, you should change the row banding size to 1 in the Format Shading pane. This setting will ensure that each row has a different shading from the one above and below it, creating an alternating pattern of grey and white rows. References: The answer can be verified through practical application within Tableau or by consulting Tableau’s official learning resources, such as  Tableau Help: Format Shading  or  Tableau Training Pass: Formatting .

In Tableau dashboards, floating elements are those that can be freely moved over the dashboard canvas without being snapped into the tiled layout. The floating elements are often indicated by their standalone frames and the ability to overlap with other dashboard items. From the provided image, the state filter and the Rate of Obesity chart can be identified as floating if they can be moved independently of the tiled grid layout that constrains other elements.

The same person can appear multiple times because an individual may have won several awards. Consequently, COUNT([Name]) would count award records rather than distinct people and would overstate the number of award recipients. COUNTD([Name] ) returns the number of distinct non-null names, so each person is counted only once regardless of how many award rows are associated with that person. Tableau’s aggregate-function documentation defines COUNTD as returning the number of distinct items in a group and demonstrates its use when unique entities must be counted. MAX([Name]) returns a single maximum string value according to the applicable sort sequence. ATTR tests whether a group contains one unique value, while COVAR is a statistical covariance function requiring quantitative expressions. Therefore, C correctly counts unique award-winning people.

The target visualization shows a subtotal after the members of each Category while retaining the individual Sub-Category rows. In Tableau, Analysis > Totals > Add All Subtotals inserts subtotal rows or columns when multiple dimensions are present on Rows or Columns. Here, Category and Sub-Category are both on Rows, so Tableau can calculate a subtotal for each Category group. Show Column Grand Totals and Show Row Grand Totals create totals for the entire view along the corresponding direction; they do not insert a separate total inside every Category section. Column Totals to Top only changes the placement of existing column totals. Because the requirement is to add a Total row for Furniture, Office Supplies, and Technology individually, Add All Subtotals is the correct command.

In Tableau, the RANK function assigns a rank to each row within a partition of the data, based on the value of the field being ranked. It is important to understand that the rank is recalculated whenever the underlying data or the partitioning changes.

In the given scenario, the Overall Rank is based on the Sales figures, while the Rank (presumably) is based on the Sales within the Category. When filtering on the condition where [Overall Rank] - 1, it means we are excluding the sub-category that has an Overall Rank of 2.

Looking at the data:

Furnishings has an Overall Rank of 8, which does not meet the filter condition ([Overall Rank] - 1). Therefore, its rank remains the same.

Tables have an Overall Rank of 3. When the sub-category with an Overall Rank of 2 is removed (Chairs in this case), Tables move up in the overall ranking. However, since Tables are the top-ranked within the Furniture category, their Rank within the category would remain unchanged at 1.

Chairs have an Overall Rank of 2, which meets the filter condition and thus will be removed from the view. We cannot determine the change in Rank for Chairs because they are filtered out.

Accessories have an Overall Rank of 5. If any sub-category with a higher Overall Rank (1 to 4) is removed, the rank of Accessories within the Technology category could change because it is currently ranked 3 in its category. With the removal of Phones (Overall Rank 1), the Rank of Accessories could potentially increase.

Copiers have an Overall Rank of 6, which does not meet the filter condition. Therefore, its rank remains the same.

Machines have an Overall Rank of 4. If we remove Phones (Overall Rank 1), Machines will move up in the overall ranking and potentially within the Technology category as well, changing its Rank from 2 to 1.

Phones have an Overall Rank of 1, which does not meet the filter condition of being Overall Rank 2. Therefore, its rank remains the same.

Bookcases have an Overall Rank of 7, which does not meet the filter condition. Therefore, its rank remains the same.

Based on this analysis, when the sub-category with an Overall Rank of 2 (Chairs) is removed, the Rank value will change for Tables, Accessories, and Machines, as they will move up in the overall ranking within their respective categories. However, it ' s important to note that while Tables will move up in the overall ranking, their rank within the Furniture category would not change as they are already at the top. The rank changes for Accessories and Machines are due to the removal of Phones, which is ranked higher overall and within the Technology category.

A URL action is Tableau’s mechanism for opening an external web page or web-based resource from a worksheet or dashboard. Because the requirement says the page must open when the user clicks the sheet, the action should be configured as Go to URL with Run action on set to Select. Select runs the action when the user clicks a mark, while Menu requires the user to open a context or tooltip menu and choose the action explicitly. A navigation button and a Go to Sheet action move between Tableau sheets or dashboards rather than opening an external webpage. A Web Page object embeds web content within a dashboard and does not satisfy the requirement to open the specific page in the default browser when the sheet is clicked. Therefore, option C is the appropriate configuration.

Publishing the Excel-based goals data as its own managed data source provides the most appropriate architecture for a file that must be updated regularly and reused alongside an existing published revenue source. The analyst can publish the Excel connection as an extract and configure the appropriate refresh mechanism, after which the dashboard workbook connects to both centrally governed published sources. Tableau documents that published extract data sources can be refreshed on a schedule and that every connected workbook then benefits from the refreshed data. Merely embedding an Excel extract in one workbook would couple refresh management to that workbook, while simply uploading a flat file through web authoring does not guarantee updates to the original changing file. Modifying the ERP system is unnecessary. Therefore, option D provides the intended reusable and maintainable Tableau design.

To unsubscribe from the views, you should use the My Content area of Tableau web pages. This area allows you to manage your subscriptions, as well as your workbooks, views, and data sources. You can select the views you want to unsubscribe from, click Actions, and then click Unsubscribe. You can also change the subscription options, such as the schedule, the format, or the message. References:

Create a Subscription to a View or Workbook - Tableau

Tableau Certified Data Analyst Study Guide

A data source filter is a filter that applies to all the worksheets that use the same data source. It filters the data before any other filters or calculations are applied. You can add a data source filter from the Data Source page by clicking on the Add button next to Filters.

The type of filter that will appear in the Edit Data Source Filters dialog box is a dimension filter on all the sheets. This means that you can choose a dimension from your data source and filter it by values, range, condition, or top/bottom. The filter will affect all the worksheets that use that dimension.

The other types of filters are not data source filters and will not appear in the Edit Data Source Filters dialog box. A table calculation filter is a filter that applies to a table calculation, such as percent of total or running total. A top N condition filter is a filter that shows only the top or bottom N values of a measure or dimension based on a condition. A context filter is a filter that creates a subset of data that other filters can use.