Explanation

In Tableau dashboards, adding an export button for users to download the entire dashboard as an image (e.g., PNG) is a built-in feature designed for easy sharing. This is achieved by dragging a specific object from the Objects pane onto the dashboard canvas. Only one object type directly enables this functionality without custom coding.

Correct Option:

✅ C. Download
The Download object is the precise tool for this task. Once added to the dashboard (via Objects pane → Download), it appears as a button that users can click. In the dialog, they select "Dashboard" and "Image" format, exporting the full view with filters applied. It's interactive and respects the dashboard's layout.

Incorrect Options:

❌ A. Navigation
The Navigation object creates buttons or buttons for switching between worksheets, sheets, or other dashboards within the workbook. It facilitates movement inside the project but has no export capabilities, so it cannot generate an image file of the dashboard.

❌ B. Image
This object lets you insert static images (e.g., logos, charts from external sources) onto the dashboard for visual enhancement. It's purely for display and embedding; it does not provide any interactive export features or buttons for downloading content.

❌ D. Extension
Extensions allow integration of custom web-based apps or third-party tools via JavaScript APIs, often for advanced features like embedding videos. While powerful, they require development and are not the simple, native way to add a built-in image export button.

Reference:
Tableau Official Help – Create a Dashboard
Export Dashboards as Images: https://help.tableau.com/current/pro/desktop/en-us/export_images.htm

Explanation

A dynamic filter requires a parameter whose data type aligns with the field it is filtering. To match common categorical or ID-based data (like Region, Product ID, or Customer Name), the parameter must be able to store text labels or whole numbers. Decimal numbers, true/false values, or specific dates would not be suitable for filtering these common categorical fields.

Correct Options

✅ E. String:
A String parameter is ideal for filtering data based on text fields, such as Category Names, Regions, or Statuses. Users can select from a list of text values (e.g., "Furniture," "Technology," "Office Supplies") to dynamically show only the relevant records.

✅ F. Integer:
An Integer parameter is perfect for filtering data based on whole number fields, such as Product ID, Year, or Quantity. It allows users to select a specific number to filter the dataset, making it dynamic and interactive for numerical categories.

Incorrect Options

❌ A. Float:
A Float (decimal) parameter is used for continuous numerical values. It is not suitable for filtering typical categorical data, as it can accept values like 10.5, which rarely correspond to discrete categories or IDs in a filter context.

❌ B. Boolean:
A Boolean parameter is restricted to only two values: True or False. This is too limited to produce a dynamic filter across multiple categories like various product types or region names shown in the results.

❌ C. Date:
A Date parameter is specific for filtering date fields. Since the results show categorical data (not temporal data), a date type is not the appropriate choice for this filtering scenario.

❌ D. Datetime:
A Datetime parameter is used for precise timestamp data. It is not relevant for filtering standard categorical or ID-based information, as it deals with dates and times down to the second.

Summary
String and Integer parameters are used to filter categorical and whole-number data dynamically. Float, Boolean, Date, and Datetime types are mismatched for this purpose.

Reference
Tableau Help: Create Parameters

Explanation

To logically arrange multiple tables in the Data pane, you need a feature that groups the underlying fields (dimensions and measures). This organization makes complex data sources more navigable and intuitive for the analyst, allowing for a cleaner workspace and improving efficiency during report development.

Correct Option

✅ A. Folders:
Folders are the primary tool for organizing fields within the Data pane. You can create folders for dimensions, measures, or even custom categories like "Marketing Data" or "Sales Tables." This directly addresses the need to group tables based on their data type, decluttering the view and making specific fields easier to locate.

Incorrect Options

❌ B. Hierarchies:
Hierarchies are for drilling down within a single dimension (e.g., Year > Quarter > Month). They do not organize multiple tables or their fields into groups. Their function is related to data exploration, not Data pane structure.

❌ C. Sets:
Sets are custom, static subsets of data created from a single dimension based on specific conditions. They appear as their own objects in the Data pane but are not used to categorize or organize the tables or fields from those tables.

❌ D. Groups:
Groups combine multiple, related dimension members into a single, higher-level item (e.g., grouping city names into regions). This affects how data is visualized in a view but does not reorganize the physical structure of the tables in the Data pane.

Summary
Folders are used to organize fields from tables logically. Hierarchies, sets, and groups are used for data relationships, subsets, and dimension member consolidation, respectively.

Reference
Tableau Help: Organize Fields in the Data Pane

Explanation

If you want a parameter to toggle which measure is shown (Sales or Profit), the parameter typically stores text values — e.g. “Sales” or “Profit”. The calculated field (Selected Measure) then uses a CASE statement checking those text values, returning the appropriate measure. That is exactly what option D shows: when the parameter equals "Sales" return the Sales measure, when it equals "Profit" return Profit. This matches the documented pattern for measure swapping in Tableau.

Why 🟢 D is correct

Because the parameter values should match what you define in the CASE statement (strings “Sales”, “Profit”), the correct formula must compare the parameter to those strings. Option D does that directly: CASE [Pick Measure] WHEN "Sales" THEN [Sales] WHEN "Profit" THEN [Profit] END. This is the standard and recommended approach for dynamic measure switching in Tableau.

❌ Why the other options are incorrect

🔴 A. Case [Pick Measure] WHEN 1 THEN [Sales] WHEN 2 THEN [Profit] END
This assumes the parameter returns numeric codes (1 or 2), but in a typical “Pick Measure” parameter you store the measure names (e.g. “Sales”, “Profit”), not numeric codes. Unless your parameter was set up with numeric values, this won’t match the parameter’s values — so it fails.

🔴 B. Case AVG([Pick Measure]) WHEN [Sales] THEN 1 WHEN [Profit] THEN 2 END
This makes no sense because it treats the parameter as a measure to aggregate (AVG), and then tries to compare aggregated value to measure fields. That’s not how parameter‑driven measure selection works in Tableau. Parameter values are constants (not aggregated measures); and the calculated field should return a measure value, not a numeric code.

🔴 C. Case [Pick Measure] WHEN [Sales] THEN 1 WHEN [Profit] THEN 2 END
This version compares parameter to measures (not to the parameter’s textual values), and returns numeric codes (1 or 2) rather than the actual measure value. That means when the parameter value matches — which it won’t — you’d get a number rather than the measure. So it won’t switch between actual measures.

🔗 Reference
Tableau Help — “Swap Measures Using Parameters” documentation

Explanation

The new data source already combines actual costs and budgets in one place, so the goal is to switch the entire workbook to this improved source without rebuilding visualizations. Tableau provides a native feature that swaps the old source for the new one across every sheet and dashboard in seconds, preserving all calculations, formatting, filters, actions, and layout.

✅ Correct Option: D
Edit the existing workbook on the Tableau site and connect to the new data source. From the Data menu, choose Replace Data Source. This is the fastest and safest method. Replace Data Source globally updates every worksheet and dashboard to use the new published source in one click. All field mappings that match by name carry over automatically, and the dashboard looks exactly the same while now showing budget data alongside actuals.

❌ Incorrect Option: A
Create a copy of the existing workbook, open it in Tableau Desktop, and connect to the new data source. Update each sheet manually. This approach requires opening Desktop and manually remapping fields on every single sheet. It’s unnecessarily labor-intensive when a perfect replacement source already exists and can be swapped instantly online.

❌ Incorrect Option: B
Edit the existing workbook on the Tableau site and connect to the new data source. Blend the new data source with the existing one. Blending is meant for combining separate sources with different granularity. Since the new source already contains everything needed, blending would add complexity, risk mismatched results, and hurt performance for no benefit.

❌ Incorrect Option: C
Create a new workbook in Tableau Desktop and connect to the new data source. Copy and paste all the tabs from the old workbook into the new one. Copy-pasting sheets breaks dashboard actions, layout containers, device-specific designs, and published permissions. It also creates duplicate content on the server and is far more work than a simple source replacement.

Summary
Replace Data Source is the official, one-click solution when the new source contains all required fields. It preserves 100% of the existing workbook structure and appearance. All other options create unnecessary rework or technical debt.

Reference
Tableau Official Documentation – Replace Data Sources
Tableau Online Help – Editing Published Workbooks