Salesforce Certified Tableau Desktop Foundations — Practice Set 2

Question 1

A financial analyst refreshes an extract each morning before the market opens, but the source database updates continuously throughout the day. What is a direct consequence of this workflow?

Accepted Answer

Extracts are static snapshots taken at refresh time; until the extract is refreshed again, the workbook reflects only the data as of that last refresh, regardless of ongoing changes at the source. Tableau does not auto-switch connection types, does not block opening a workbook with a stale extract, and does not swap file formats on its own.

Question 2

An author wants to reuse a fully configured connection — including calculated fields and aliases — across several new workbooks without duplicating the underlying data each time. What should the author save?

Accepted Answer

A .tds file stores the data source's connection metadata and customizations (calculated fields, aliases, etc.) without embedding the raw data, so it can be reused across multiple workbooks efficiently. A .twbx bundles both workbook and data; a .hyper file is the extract's data engine format; a .png is a static image export.

Question 3

A team maintains an Orders table and a Returns table with the same grain (one row per order line) and wants both tables to behave as one flattened table so that a single worksheet view can filter and aggregate across both simultaneously. Which technique is most appropriate?

Accepted Answer

When two tables share the same grain and need to be treated as one combined, flattened table for row-level analysis, a join is the appropriate technique. A relationship deliberately preserves each table's separate level of detail rather than flattening them, which isn't what's needed here. A parameter doesn't combine tables, and a geographic role only affects how a field is mapped.

Question 4

A field named 'order_dt' is imported as a text string instead of a date. What should the author do so Tableau treats it correctly for date-based analysis?

Accepted Answer

Changing a field's data type to Date tells Tableau to interpret its values as dates, enabling date-specific functions, drill-downs, and continuous/discrete date behavior. Renaming only changes the display label, a geographic role is for location-based mapping, and adding a field to a hierarchy organizes drill-down levels but doesn't fix its underlying data type.

Question 5

A dataset stores product prices as whole numbers representing cents (e.g., 1999 for $19.99). Which default field property should the author adjust so values display correctly as currency?

Accepted Answer

Adjusting a field's default number format (e.g., to currency with the appropriate decimal handling) controls how its values are displayed across the workbook wherever that field is used. Geographic role is unrelated to numeric display, hierarchy level concerns drill-down organization, and connection type refers to how Tableau accesses the source system, not display formatting.

Question 6

An author needs each distinct customer segment value (e.g., 'Consumer', 'Corporate') to display with a more business-friendly label (e.g., 'Retail Customers') without changing the underlying data values. What should the author use?

Accepted Answer

Assigning an alias changes the displayed label for a specific data value without altering the underlying stored value, which is exactly what's needed for cosmetic relabeling. Creating an extract only affects data storage/performance, a union stacks rows from similarly structured tables, and changing data type would affect how the field is processed, not its display label.

Question 7

A sales manager wants to see revenue trends over the past two years plotted as a single continuous line across months. Which chart type is most appropriate?

Accepted Answer

A line chart connects data points across a continuous dimension (typically a date field) making it ideal for visualizing trends over time. A density map shows concentration of geographic points, a stacked bar sums categorical segments within bars, and a highlight table is a color-coded crosstab, none of which are suited to a continuous time trend.

Question 8

An analyst wants a single view showing SUM(Sales) as bars and the count of Orders as a line, both on the same set of category headers but scaled to a shared single axis so their relative proportions are visually comparable on the same scale. What chart type fits this description?

Accepted Answer

A combined axis chart plots multiple measures against a single, shared axis, which is appropriate when values should be compared directly on the same scale. A dual axis chart instead gives each measure its own independent scale — useful when magnitudes differ greatly, but not when a shared scale is explicitly wanted. Scatterplots compare two measures as points, and density maps are geographic.

Question 9

Which chart type would best help identify geographic hotspots of customer density from thousands of individual transaction locations plotted on a map?

Accepted Answer

A density map uses color intensity to show where geographic points cluster most heavily, which is effective for visualizing hotspots among a large number of location-based marks. A crosstab is a numeric table without spatial context, a line chart shows trends over a continuous dimension, and a dual axis chart compares two measures on separate scales rather than geographic density.

Question 10

A marketing analyst wants to define a dynamic collection of 'Top 10 Customers by Sales' that automatically updates as the underlying data changes, so it can be used to compare those customers against everyone else. Which feature should be used?

Accepted Answer

Sets define a custom, often condition-based or top-N membership (like 'Top 10 Customers by Sales') that can automatically recompute as data changes, and are commonly used to compare in-set vs. out-of-set members. Groups combine specific, typically static dimension members without conditional top-N logic; hierarchies organize drill-down levels; aliases only relabel display values.

Question 11

A dashboard consumer wants to filter a view to only show orders placed within the last 30 days, updating automatically each day it is viewed. Which filter type accomplishes this?

Accepted Answer

A relative date filter defines a rolling window relative to the current date (e.g., 'last 30 days') and automatically recalculates each time the view is opened. A fixed date range filter would need manual updates to stay current; a quick table calculation performs computations like running totals rather than filtering rows; a reference line only annotates a value on an axis.

Question 12

An analyst wants to segment continuous Age values into fixed-width groups (e.g., 0-9, 10-19, 20-29) to build a histogram of customer age distribution. What should the analyst create?

Accepted Answer

Bins divide a continuous measure into fixed-size intervals, which is the standard technique for building a histogram of a distribution like customer age. Parameters are user-adjustable inputs, sets define custom conditional membership, and groups combine existing categorical (dimension) members rather than segmenting a continuous numeric range.

Question 13

Which of the following are examples of quick table calculations available in Tableau Desktop? (Choose two.)

Accepted Answer

Running total and percent of total are both built-in quick table calculations that can be applied directly to a measure in the view to recompute values based on the table structure. Geographic role assignment is a field property for mapping, not a table calculation, and a data source alias only relabels a value's display, unrelated to table calculations.

Question 14

An analyst wants end users to be able to type in any target sales figure and instantly see a reference line move on the chart to reflect that value. What two features work together here?

Accepted Answer

A parameter accepts free-form user input (like a typed target value), and a calculated field can reference that parameter to dynamically position a reference line based on the entered value. Bins and hierarchies concern segmenting/organizing existing categorical or numeric fields, not accepting typed input; groups and filter actions relate to dimension membership and cross-worksheet filtering, not typed numeric targets.

Question 15

A finance team wants to see a grand total row appended below regional subtotal rows in a crosstab view. Which feature should be enabled?

Accepted Answer

Show Totals adds grand total and/or subtotal rows/columns summarizing the values already displayed, which directly satisfies the request for an appended grand total row. The data highlighter searches and highlights marks, viz animations transition between visual states, and a story point is a narrative slide — none of which add total rows to a crosstab.

Question 16

A dashboard author wants each mark in a scatterplot to be represented by a distinct icon shape (e.g., circle vs. square) depending on customer segment, rather than by color. Which Marks card property should be used?

Accepted Answer

The Shape property on the Marks card assigns different icon shapes to marks based on a dimension's values, which is exactly what's needed to distinguish customer segments by shape rather than color. Detail adds granularity to marks without a visual shape/color encoding, Label displays text on marks, and Tooltip controls hover-over detail text.

Question 17

An author wants clicking a bar in one worksheet to open a related external web page (such as a product page) that includes the selected value in the URL. Which dashboard action should be configured?

Accepted Answer

A URL action opens a specified web address, optionally inserting selected field values into the URL, when a user interacts with a mark — ideal for linking to an external page. A filter action instead updates other worksheets' filters; a highlight action visually highlights related marks; a parameter control is a UI widget for manually setting a parameter, not for opening links.

Question 18

A dashboard needs to look and function well on both desktop browsers and mobile phones, with different worksheet arrangements for each. What feature should the author configure?

Accepted Answer

Tableau lets authors configure device-specific dashboard layouts (desktop, tablet, phone), each with its own arrangement of objects optimized for that screen size. A single fixed-size layout wouldn't adapt well across devices, story points are for narrative sequences rather than responsive layout, and there's no parameter mechanism to toggle layouts by device.

Question 19

A presenter wants to build a guided, sequential narrative that walks stakeholders through several dashboard states, one slide at a time, each captured at a specific point in the analysis. What should the presenter create?

Accepted Answer

A story is a sequence of worksheets or dashboards, called story points, that presents a narrative walkthrough of an analysis one captured state at a time. Sets define custom membership, parameter controls are interactive input widgets, and bins group continuous values — none of these build a sequential narrative presentation.

Question 20

A user wants to inspect the exact row-level records that make up an aggregated bar in a view before deciding whether to export them. What should they do?

Accepted Answer

Viewing the underlying data for a selected mark shows the individual, disaggregated records that were summarized to produce that mark, and from there the data can optionally be exported. Changing the default aggregation would alter the calculation for the whole field, a reference line only annotates a value, and creating a hierarchy affects drill-down organization, not row-level inspection.

Question 21

A vendor wants to send a colleague only the raw values behind a Tableau view, in a format that can be opened in Microsoft Excel or another spreadsheet tool, without any Tableau-specific formatting. What is the most direct approach?

Accepted Answer

Exporting the underlying data to a plain format like .csv provides just the raw values in a form easily opened by spreadsheet tools, without Tableau-specific visual formatting. Publishing to Server requires server access rather than a portable file for a colleague without Tableau; a .twbx file is a full interactive workbook, not a plain data export; a calculated field has nothing to do with exporting data.

Question 22

In Tableau, which category of field typically contains quantitative, numeric values intended to be aggregated, such as Sales or Quantity?

Accepted Answer

Measures are quantitative fields meant to be aggregated (summed, averaged, counted, etc.), such as Sales or Quantity. Dimensions instead hold qualitative, categorical data used for segmentation. Filters restrict which data is shown rather than describing a field category, and hierarchies organize related dimensions into drill-down levels.

Question 23

A continuous field placed on an axis in Tableau is rendered using which visual treatment?

Accepted Answer

Continuous fields render as a smooth, unbroken axis (shown in green in Tableau's field pills), suitable for measures or continuous date values. Discrete fields, by contrast, render as distinct separated headers (shown in blue). A color legend or filter card describes other view elements, not the discrete/continuous rendering distinction itself.

Question 24

An author drags Order Date onto Columns and chooses the continuous 'Month' date value (rather than the discrete date part). How does this affect the resulting axis compared to using the discrete date part?

Accepted Answer

A continuous date value plots each month/year combination as its own point along a single unbroken timeline (e.g., Jan 2024 and Jan 2025 appear separately), whereas the discrete date part groups same-named periods together across years (all Januarys combined). The field's fundamental type (a date, not a measure) doesn't change, and it certainly doesn't disappear from the view.

Question 25

A worksheet shows AVG(Sales) with no dimensions in the view. After the author adds Customer Segment to Rows, the displayed average(s) change. What best explains this behavior?

Accepted Answer

Adding a dimension to the view changes the granularity at which an aggregated measure is computed — Tableau recalculates AVG(Sales) independently for each distinct value of Customer Segment rather than repeating a single overall average. Tableau does not automatically swap aggregation types, and Customer Segment remains a dimension rather than being converted.

Analytics-101 — Salesforce Certified Tableau Desktop Foundations