Explanation:

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.

Explanation:

The task requires creating a filled map (also known as a choropleth map) in Tableau Desktop to visualize the distribution of total Sales by State across the United States, using the Sample - Superstore data source in the Map worksheet of the Book1 workbook. A filled map uses color shading to represent the value of a measure (here, total Sales) across geographic regions (here, U.S. states). Below is a detailed explanation of the task, why it’s relevant for the Salesforce Tableau Data Analyst Exam, and how to execute it, addressing the provided options and their irrelevance.

Context and Purpose:
➡️ Objective: The goal is to create a visualization that shows how total Sales vary across U.S. states, with each state shaded according to its sales value. This helps identify geographic patterns, such as which states have higher or lower sales.
➡️ Data Source: The Sample - Superstore dataset, a standard dataset in Tableau, includes fields like State (a dimension with a geographic role for U.S. states), Sales (a measure), and others like Category or Profit. It’s commonly used in Tableau training and certification exams.
➡️ Worksheet: The Map worksheet in the Book1 workbook is the target location for the visualization.
➡️ Relevance to Exam: This task aligns with the “Create Content” section (26% of the Salesforce Tableau Data Analyst Exam), which tests skills in building visualizations, including maps, to represent data distributions effectively.

Why a Filled Map?
A filled map is ideal for showing the distribution of a measure (Sales) across geographic areas (States). Each state is filled with a color, where the shade or intensity represents the magnitude of total Sales (e.g., darker shades for higher sales).
Tableau automatically recognizes the State field in the Superstore dataset as a geographic field, enabling map creation without additional configuration.
The filled map provides a quick, intuitive way to compare sales performance across states, useful for business analysis (e.g., identifying high-performing regions).

Steps to Create the Filled Map:

Here’s how to accomplish the task in Tableau Desktop:

1. Open the Workbook:
Locate the Book1 link on your desktop and double-click to open it in Tableau Desktop.
This loads the workbook, which should include the Sample - Superstore data source.

2. Navigate to the Map Worksheet:
At the bottom of the Tableau interface, find the Map worksheet tab and click to open it.
If the worksheet already contains a visualization, you can modify it; if blank, you’ll build the map from scratch.

3. Verify the Data Source:
In the Data pane on the left, ensure the Sample - Superstore data source is selected. Look for fields like State (under Dimensions, with a globe icon indicating its geographic role) and Sales (under Measures).

4. Create the Filled Map:
➡️ Add State to the View:
Drag the State field from the Data pane to the Detail shelf in the Marks card (or drop it directly onto the worksheet canvas).
Tableau recognizes State as a geographic field and generates a map view, initially with symbols (e.g., circles) for each state.

➡️ Change to Filled Map:
In the Marks card, click the mark type dropdown (initially set to Automatic or Circle) and select Map. This converts the visualization to a filled map, where each state is a filled shape.

➡️ Add Sales to Color:
Drag the Sales measure from the Data pane to the Color shelf in the Marks card.
Tableau automatically aggregates Sales as SUM(Sales), coloring each state based on its total sales. A color gradient (e.g., light to dark) appears, with a legend showing the sales range.

5. Customize the Visualization:
➡️ Color Palette:
Click the Color shelf, then Edit Colors. Choose a gradient palette (e.g., Blue, Orange-Gold, or Green) to represent sales. Select Reversed if you want higher sales to appear darker.

➡️ Labels (Optional):
Drag Sales to the Label shelf to display sales values on each state.
Format labels by clicking Label > Format, selecting Currency (Standard) or $#,##0 for readability.

➡️ Map Layers:
Go to the Map menu > Map Layers.
Adjust Washout to make state boundaries clearer, enable State/Province Borders, or add other map features like coastlines.
Ensure the map is zoomed to the United States (use Map > Map Options or zoom manually).

➡️ Tooltip:
Click the Tooltip shelf and edit to include fields like State and SUM(Sales) (e.g., “State: , Total Sales: $<SUM(Sales)>”) for user interaction.

➡️ Filter Non-U.S. Data (if needed):
If the Superstore dataset includes non-U.S. data (e.g., Canada), drag Country to the Filters shelf and select United States.

6. Finalize and Save:
Double-click the worksheet title and rename it (e.g., “Total Sales by State”).
Verify the map shows U.S. states shaded by total Sales, with a color legend indicating the range.
Save the workbook to preserve changes.

Result:
The filled map displays each U.S. state shaded according to its total Sales from the Superstore dataset. For example:
🧩 States with high sales (e.g., California, New York) might appear in darker shades.
🧩 States with low sales might appear in lighter shades.
🧩 Hovering over a state shows a tooltip with the state name and total sales.
🧩 The color legend on the right indicates the sales range (e.g., $0 to $500,000).

Explanation:

✅ Correct Answer: C. Right-click on the rightmost dimension, choose Sort, then select nested in the options.
This is the correct approach when you want to sort values like Sales across multiple dimensions in Tableau (e.g., Region → Category → Sub-Category). In Tableau, sorting is hierarchical when multiple dimensions are placed on Rows or Columns. To preserve this hierarchy while sorting based on a measure like Sales, you must sort within each level rather than globally. This is done through a nested sort, which means Tableau will sort each instance of the lower-level dimension (the rightmost one on the shelf) within the context of the higher-level dimensions. You apply this by right-clicking on the last dimension in the hierarchy (e.g., Sub-Category), choosing Sort, then selecting Field, choosing Sales as the sorting field, and enabling Nested sort. This maintains the proper grouping structure while ordering values correctly within each group.

❌ Option A: Use the Sets feature to combine dimensions and then sort one of the fields.
Sets in Tableau are used primarily for comparing subsets of data or creating dynamic groups based on conditions or selections. While they are powerful tools for filtering and segmenting data, they are not intended for sorting purposes. Sets can define which data is in or out of focus, but not how that data is ordered across a hierarchical structure. Trying to combine multiple dimensions into a set and then sort one of the fields would not produce the desired nested or contextual sort needed across multiple dimensions. Furthermore, sets are binary in nature (i.e., a value is either in the set or not), which makes them unsuitable for ranking or ordering operations across a complex hierarchy.

❌ Option B: Use the Group feature to combine dimensions and then sort the grouped field.
Groups in Tableau are used to manually combine members of a dimension into higher-level categories. For example, you might group several states into a region. While this can simplify a view or reduce the number of members in a dimension, it is not a sorting mechanism. Grouping changes the data structure by altering categories but doesn't provide dynamic control over sorting based on a measure like Sales. Also, once dimensions are grouped, the ability to sort within the original granular levels is lost, defeating the purpose of sorting "across multiple dimensions." Using groups might even mask useful variations in data that you'd want to highlight with a proper sort.

❌ Option D: Right-click on each dimension, choose Sort, then select data source order in the options.
Sorting each dimension individually and selecting data source order simply preserves the original order from the data source, which is not necessarily meaningful or useful for analytical sorting. This method does not allow for sorting based on any measure (such as Sales), nor does it consider the hierarchical relationships between dimensions. If you're dealing with multi-level data and want to see, for example, the highest-grossing Sub-Categories within each Category and Region, sorting by data source order on each field will not produce that result. Instead, it may give a confusing or inconsistent view of the data because it ignores the context needed for nested sorting.

📘 Summary:
To sort data across multiple dimensions based on a measure like Sales, you must use nested sorting on the rightmost dimension in the visual hierarchy. This ensures the sort respects the structure and context of the data. Sets and Groups are used for categorization and filtering—not sorting—and data source order does not reflect analytical priorities.

🔗 Reference:
ℹ️ Tableau Official Docs – Sorting Data
ℹ️ Tableau Video – Sorting Data

Explanation:

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.