Explanation:

Open the CC workbook in Tableau Desktop and go to the worksheet named Incremental.
In the Data pane, right-click on [Product Name] (or the dimension currently on Rows) and choose Show Quick Filter (optional, for verification later).
From the Analytics pane (left sidebar), drag Table Calculation onto the view.
In the dialog that opens, select Running Total.
Change the following settings:
Compute Using → Table (Across) or Specific Dimensions → [Product Name] (depending on current sort)
Check the box Add secondary calculation
Secondary Type → Percent of Total
Secondary Compute Using → Table (Down) or Specific Dimensions → [Product Name]
Click OK.
You now have a running-total measure. Right-click this pill on the view and choose Quick Table Calculation → Running Total (if not already applied).
Right-click the same pill again → Add Secondary Calculation → Percent of Total.
Right-click the axis → Add Reference Line.
Choose Line
Value → the running-total percent pill
Label → None or Value if desired
Formatting → make it a different color (usually red) and slightly thicker
(Optional but typical for Pareto) Right-click the secondary axis on the right → Dual Axis, then right-click again → Synchronize Axis.
On the Marks card, change the primary mark type to Bar (for incremental sales) and the secondary mark type (the one with the running % pill) to Line.
Clean up:
Hide the right-hand axis (right-click → uncheck Show Header)
Format the line (color, thickness, etc.)
Add axis titles if needed (“Cumulative % of Sales”)
From the menu, click File → Save.
You now have the classic Pareto chart: bars showing incremental sales by product (sorted descending) and a red line showing the cumulative percentage contributed by each product. This is the exact requirement for the Analytics-Con-301 hands-on exam section.

Explanation:

Why:
In Tableau (and most compute engines), operations on simpler, smaller types are cheaper.

Boolean logic is minimal (true/false), so it evaluates quickest.
Integers are numeric and efficient for arithmetic/comparisons.
Strings require more work (collation, length, encoding), so they’re slowest for comparisons/joins/aggregations.

Tip:
When possible, model flags as Boolean or integer keys instead of strings to improve calc, filter, and join performance.

Explanation:

Why it’s correct:
Tableau Catalog (which is included in the Data Management Add-on) provides the features the client wants: data lineage, impact analysis, metadata/data dictionary, curation, and data quality warnings—all across connected sources like data lakes and the Tableau environment.

Why the others aren’t:
A. Tableau Catalog without Data Management Add-on: Tableau Catalog is part of the Data Management Add-on; you don’t get Catalog without it.
C. Tableau Prep Conductor: Used to schedule/monitor Prep flows, not to provide cataloging/lineage for assets.
D. Tableau Catalog with Tableau Server Management Add-on: Server/Advanced Management focuses on security, manageability, scalability—not lineage/collaboration metadata.

Explanation:

A Sankey diagram is not a native chart type in Tableau.
To build one easily—especially for non-expert users—you use a Viz Extension.

Why Viz Extensions?
Sankey charts require complex data prep (path curves, table calcs, densification).
Tableau Cloud does support sandboxed Viz Extensions.
Tableau Exchange includes Sankey-style extensions such as:
- Sankey Diagram Extension
- Advanced Sankey & Network Graph Extensions

These allow users to drag and drop fields to produce a Sankey without custom calculations, which fits the shipping clerk’s need for a direct and easy workflow.

Therefore, A is correct.

❌ Why the Other Options Are Wrong

B. Use Show Me
Tableau Show Me does NOT include Sankey as a chart type.
Users cannot build a Sankey using Show Me.

C. Download an Accelerator
Accelerators provide prebuilt dashboards, not new chart types.
They do not provide Sankey visualizations unless specifically designed for the dataset.
They do not create custom chart types like Sankeys.

D. Download a Connector
Connectors are used to bring in data from external systems.
They do not create visualizations.

Explanation:

Why C Is the Correct Choice

The requirements are: (1) row-level security by territory, (2) fully automated for a large team with high turnover, (3) no manual maintenance of hundreds of users, and (4) no Tableau Data Management license.

The only solution that satisfies all of these without Data Management is the classic entitlements-table approach (also called “user-based row-level security with a join”):

A simple entitlements table is maintained in the database (or CSV/Excel) with two columns: Username (or email) and Territory.
Join this table to the sales fact table on Territory.
Add a data source filter: [Username] = USERNAME() (or [Email] = USERNAME() in Tableau Cloud).
Publish this single secured data source.

When any sales rep opens the dashboard, Tableau automatically filters the data to only the rows matching their login—no groups, no manual user filters, no separate workbooks. New hires or territory reassignments are handled by updating one row in the entitlements table; no Tableau Server admin work is required.

Why the Other Options Are Incorrect

A. Create one group per territory and map groups
This works but fails the “automated + high turnover” requirement. With dozens or hundreds of territories and frequent reassignments, the admin would constantly be moving users between groups—extremely labor-intensive and error-prone.

B. Create separate workbooks per territory
This is the least scalable and most maintenance-heavy option. Every territory change requires republishing workbooks and updating project-level permissions. It also fragments content and prevents a single unified “Sales Dashboard.”

D. Create a user filter in the workbook and manually map each user
Workbook-level user filters require the workbook author to manually maintain a giant list of every sales rep and their territory inside the calculation (e.g., USERNAME() = "john.doe@company.com" AND [Territory] = "West" or a huge CASE statement). With high turnover this list becomes unmanageable within hours and is exactly what Tableau warns against.

References

Tableau Help → Row-Level Security with User Filters → “Entitlements table method (recommended when you do not have Data Management)”
Tableau Blueprint → Governance → “Managed Self-Service without Data Management” – explicitly recommends the join + data-source-filter pattern for large, dynamic teams.
Tableau Knowledge Base article #000029456: “Best practices for RLS with high user churn” – states the entitlements table is the only low-maintenance option when Data Management is not licensed.

Answer: C is the only scalable, automated, and supportable solution that meets all of the stated constraints.