Tableau TDA-C01 Practice Test Questions, Exam Dumps

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TDA-C01 Tableau Practice Test Questions and Exam Dumps

Question No 1:

You are the owner of an alert. You receive an email notification that the alert was suspended. From where can you resume the suspended alert?

A. The My Content area of Tableau web pages
B. The Data Source page of Tableau Desktop
C. The Notifications area of Tableau Prep
D. The Shared with Me page

Correct answer: A

Explanation:

In Tableau, alerts are notifications that are triggered based on specific conditions or thresholds being met, often related to the data in your dashboards. If an alert is suspended, it means that the conditions that would normally trigger the alert are temporarily disabled. As the owner of the alert, you can resume or manage this alert through the Tableau web interface.

The correct place to resume a suspended alert is the My Content area of Tableau web pages. This is where you manage your own alerts and other content, including resuming, editing, or deleting alerts. The My Content area is specific to the user and provides access to any content they own or have created, including data sources, workbooks, and alerts.

Option A is correct because the My Content area on the Tableau web interface is the designated location where you can manage your alerts, including resuming or stopping them. This area contains all personal content, including alerts that you may have set up, and from here, you can interact with them.

Option B, the Data Source page of Tableau Desktop, does not involve alert management. Alerts are generally managed through the Tableau web interface, not directly in Tableau Desktop, where you typically interact with data sources, workbooks, and reports.

Option C, the Notifications area of Tableau Prep, is also not correct. Tableau Prep is used for data preparation and cleaning tasks, and the notifications area in Tableau Prep focuses on process completion notifications, not alerts related to dashboards or visualizations.

Option D, the Shared with Me page, is incorrect as well. The Shared with Me page in Tableau web interfaces shows content that has been shared with you by others, and while it allows you to view this content, it is not where you manage your own personal alerts.

Therefore, the correct place to resume a suspended alert is in the My Content area of Tableau web pages, making A the correct answer.

Question No 2:

You have the following data source in Tableau Server. (image1) You need to ensure that the data is updated every hour. What should you select?

A. Extract Refreshes
B. New
C. Connected Workbooks
D. Connections

Correct answer: A

Explanation:

In Tableau Server, Extract Refreshes allow you to schedule updates for your data extracts. When using an extract (a snapshot of your data), you can set up a refresh schedule to update it at regular intervals. If you need the data to be updated every hour, setting up an extract refresh with that frequency ensures that the data in Tableau is regularly refreshed with the latest available data.

The other options are less relevant in this context:

B. New refers to creating a new data source or item, not updating existing data.
C. Connected Workbooks would show workbooks that are currently connected to the data source, but it does not manage the refresh schedule.
D. Connections allows you to view and manage the live data connections or the data extracts, but it does not handle the automatic refresh scheduling.

Therefore, to ensure your data is updated every hour, the correct option is Extract Refreshes.

Question No 3:

You have the following tiled dashboard that has one sheet.You want to replace the sheet with Sheet2.What should you do?

A. Right-click Sheet2 and select Add to Dashboard
B. Select Sheet3 and click the Swap Sheet button next to Sheet2
C. From the context menu of Sheet3, select Remove Dashboard Item
D. Drag Sheet2 to the dashboard
E. From the context menu of Sheet3, select Deselect

Correct answers: D

Explanation:

In a dashboard environment (likely Tableau or a similar platform), replacing an existing sheet involves adding a new sheet to the dashboard and removing or replacing the current one. Here’s why D (Drag Sheet2 to the dashboard) is the best option:

A. Right-click Sheet2 and select Add to Dashboard: While this might sound reasonable, simply adding Sheet2 to the dashboard will not automatically replace the existing sheet. You would need to manually remove the existing sheet, and this option doesn’t address replacing it directly.
B. Select Sheet3 and click the Swap Sheet button next to Sheet2: This option assumes you are using a specific feature, likely in a tool like Tableau, that allows swapping sheets directly. However, this is not a typical functionality in most dashboard tools and doesn't describe the direct action of replacing one sheet with another.
C. From the context menu of Sheet3, select Remove Dashboard Item: This option removes Sheet3 from the dashboard, but it doesn't replace it with Sheet2. It would only remove the sheet without adding the new one.
D. Drag Sheet2 to the dashboard: This is the most straightforward and effective method. By dragging Sheet2 onto the existing dashboard layout, it will automatically replace the current sheet, assuming there is no specific layout constraint preventing this action. This is the correct action to directly replace Sheet1 with Sheet2.
E. From the context menu of Sheet3, select Deselect: This action would deselect Sheet3, but it does not replace it with Sheet2. It likely just removes Sheet3’s selection from the view, which does not achieve the goal of replacing it with another sheet.

Therefore, D is the correct answer because it describes the action of replacing the existing sheet with Sheet2 by dragging it onto the dashboard.

Question No 4:

You have the following primary data source that contains a dimension named Dorm_Code. You receive the following secondary data source that contains updated dorm codes. You need to bring the updated dorm codes into Tableau and use the codes in existing visualizations.

The new dorm codes must use the existing field name of Dorm_Code. What should you do?

A. Bring in the secondary data source as a union.
B. Bring in the secondary table as a left join to the primary data source. From the Data Source page select Create Calculated Field in the Dorm_Name field and enter [Dorm_Name_New] in the calculation window.
C. Bring in the secondary data source by using relationships. From the Data pane, right-click Dorm_Name, select Replace References, and then select Dorm_Name_New.
D. Create a data blend and select Edit Primary Aliases to replace the primary data source alias values with values from the secondary data source.

Correct answer: C

Explanation:

In Tableau, when you have two data sources that need to be linked but you want to maintain the existing field names and ensure the updated data (in this case, the new dorm codes) is used, the best approach is to use relationships. Relationships allow you to define how the data from the two sources should be linked and automatically ensure that the data is joined when needed.

Let’s break down the options:

A. Bringing the secondary data source as a union is not ideal in this case because a union would stack the data vertically (combining rows from both sources) rather than updating or matching the specific dimension fields (Dorm_Code). A union is typically used when the structure of both datasets is the same and you want to append rows from one dataset to another. However, it wouldn't be effective for replacing or updating codes in the existing dimension.

B. This option suggests a left join, which could work, but creating a calculated field using [Dorm_Name_New] to replace the old codes would not solve the issue in a clean or dynamic way. The calculation might replace the names, but you still wouldn’t be linking the updated dorm codes correctly or effectively across the data sources. The join doesn’t maintain flexibility and would not automatically reflect updates or changes across visualizations.

C. This is the correct approach. Using relationships in Tableau allows you to dynamically link the two data sources based on a shared field. After bringing in the secondary data source, you can right-click on the Dorm_Name field in the Data pane, select Replace References, and then select the updated field (Dorm_Name_New) from the secondary data source. This method ensures that the updated codes are used in the visualizations and that the existing field name, Dorm_Code, is maintained, allowing Tableau to update and reflect the new values where needed.

D. Data blending involves linking two data sources based on a common field, but this option focuses on replacing alias values. While blending can be useful in certain scenarios, using relationships is a more efficient and flexible method in this case. Additionally, replacing aliases in a blend would not directly update the Dorm_Code field in the primary data source with the new values.

In conclusion, C is the best solution because it uses relationships to link the updated dorm codes from the secondary data source to the existing primary data source, ensuring that the new codes are reflected dynamically in your visualizations under the same field name.

Question No 5:

You plan to create a visualization that has a dual-axis chart. The dual-axis chart will contain a shape chart and a line chart. Both charts will use the same measure named Population on the axis.

You need to configure the shapes to be much larger than the line.What should you do?

A. Duplicate Population Drag the duplicate to the second Marks card and configure the size of the marks independently
B. For the second axis, select Shape on the Marks card. From Select Shape Palette, select Custom, and then select Reset
C. Create a custom shape that is larger than the default shape and add the shape to the Shapes folder in My Repository.
D. Change Population to a discrete dimension.

Correct answers: A

Explanation:

When working with dual-axis charts in Tableau, the ability to adjust the size of marks on each axis independently is crucial, especially when you want one chart (in this case, the shape chart) to stand out visually compared to another chart (the line chart).

In the scenario described, where you have a dual-axis chart with a line chart and a shape chart, both using the same measure (Population), the solution involves adjusting the size of the shapes relative to the line.

Option A (Duplicate Population Drag the duplicate to the second Marks card and configure the size of the marks independently):
This is the correct approach. You can duplicate the Population field, then assign one copy of the field to the line chart and the other copy to the shape chart. Once this is done, you can independently configure the size of the shapes on the second Marks card (the one used for the shape chart) to make the shapes much larger than the line. This allows you to control the relative sizing of the marks on each axis, which is precisely what the question asks for.

Now, let’s review the other options:

B. For the second axis, select Shape on the Marks card. From Select Shape Palette, select Custom, and then select Reset:
While this option describes how to select a custom shape palette, it doesn’t address the need to size the shapes independently of the line chart. It’s more about choosing different shapes, but it doesn’t help in making the shapes larger compared to the line.
C. Create a custom shape that is larger than the default shape and add the shape to the Shapes folder in My Repository:
Creating custom shapes is useful if you want to change the appearance of the shapes, but it doesn’t address the question of making the shapes larger than the line. Adjusting the size of the shapes through the Marks card is the better approach.
D. Change Population to a discrete dimension:
Changing Population to a discrete dimension would affect the chart’s granularity, but it won’t necessarily make the shapes larger than the line. This step wouldn’t address the issue of size scaling between the shape chart and the line chart.

In summary, Option A is the correct approach, as it allows you to adjust the size of the marks independently for the shape chart and line chart, ensuring that the shapes are much larger than the line.

Question No 6:

You have a line chart on a worksheet. You want to add a comment to March 2020 as shown in the following visualization. What should you do?

A. Drag the growth rate to Text on the Marks card.
B. Add a tooltip.
C. Annotate March 2020.
D. Enable captions.

Correct answers: C

Explanation:

To add a comment or label to a specific point on a line chart in Tableau (or similar data visualization tools), annotating the point directly on the chart is the best approach. Annotation allows you to place a text comment or label at a specific location on the chart, which in this case, would be for the data point for March 2020.

A suggests dragging the growth rate to the Text on the Marks card. This is a method used to display the growth rate value in a label, but it doesn’t specifically place a comment or annotation on the chart.
B suggests adding a tooltip. While tooltips are helpful for displaying additional information when hovering over a point, they are not the same as a direct annotation or comment displayed on the chart.
D suggests enabling captions, but captions are typically used for providing a description of the entire chart or worksheet, not specific data points.

C is the correct choice because annotations are designed specifically for adding comments or labels to specific points in your visualization, like March 2020 in this case.

By selecting C, you would be able to add a comment or label to March 2020 directly on the chart, ensuring that your annotation is visible and tied to that data point.

Question No 7:

You have the following dataset and need to create a specific visualization. Which quick table calculation should you apply to the Text on the Marks card?

A. Percent of Total
B. Percent Difference
C. Compound Growth Rate
D. Percentile

Correct answers: A

Explanation:

The "Percent of Total" quick table calculation is often used when you want to display each value’s contribution as a percentage of the overall total. This calculation is useful for visualizing how individual values or categories compare to the sum of all values in the dataset. If your visualization aims to show proportions or percentages of a total (for example, each category’s share of sales), "Percent of Total" would be the correct choice to drag to the Text on the Marks card.

B. Percent Difference is typically used for comparing two values or time periods, so it’s not suitable if you're aiming for proportions of a total.
C. Compound Growth Rate is used for calculating growth over time, which is not relevant if you're focusing on relative percentages of a total.
D. Percentile is used for ranking values within a distribution, not for displaying their portion of a total.

Thus, A. Percent of Total is the most appropriate quick table calculation for this scenario.

Question No 8:

A colleague provides you with access to a folder that contains the following files:

Sales.csv -
Book1.twb -
Sales.hyper -
Export.mdb -

Which file contains an extract?

A. Export.mdb
B. Sales.hyper
C. Book1.twb
D. Sales.csv

Correct answers: B

Explanation:

In the context of data tools like Tableau, a "data extract" refers to a snapshot or subset of the data, typically optimized for performance in analysis and reporting. Let’s analyze the files provided:

Sales.csv: A CSV (Comma-Separated Values) file is a text file that contains data in tabular form, but it’s not considered a data extract. It's typically a simple data file that can be read by many applications, but it does not have the optimized features of an extract.
Book1.twb: This is a Tableau workbook file, which contains the structure, sheets, and visualizations of a Tableau report. While it contains the metadata and visual layout of data, it does not contain the actual data extract. Instead, it references data connections (which could be from an extract or a live connection to a data source).
Sales.hyper: A .hyper file is a Tableau data extract file. The .hyper format is a highly optimized file format used by Tableau to store a snapshot of the data. This format allows for faster querying and analysis because the data is extracted from the original source and stored in a highly efficient way for Tableau to process. Hence, this file is the extract.
Export.mdb: An Access database (.mdb) file is a Microsoft Access database file, which contains tables, queries, forms, and other database objects. It is a relational database, not an extract.

Given the above, the correct answer is B, Sales.hyper, as this file is the actual data extract used by Tableau.

Question No 9:

You are working with a dataset in Tableau, and you need to identify the percentage contribution of each product category to the total sales. Which Tableau feature would you use to calculate this percentage?

A) Quick Table Calculation
B) Calculated Field
C) Parameter
D) Data Blending

Answer: A) Quick Table Calculation

Explanation:

Quick Table Calculations in Tableau provide an easy and fast way to perform common calculations such as percentages of the total. In this case, you would use the "Percent of Total" quick table calculation to show the percentage contribution of each product category to total sales. Quick Table Calculations can be applied to dimensions and measures and are available directly from the field’s drop-down menu in Tableau.

Question No 10:

You are visualizing sales data by region. How can you ensure that each region is highlighted with its own color in a map view?

A) Use a calculated field to assign a unique color to each region.
B) Drag the "Region" field to the Color shelf.
C) Use a parameter to select the regions to color.
D) Add "Region" to the Detail shelf for individual highlighting.

Answer: B) Drag the "Region" field to the Color shelf.

Explanation:

In Tableau, you can easily assign a unique color to each region by dragging the "Region" field to the Color shelf. Tableau will automatically generate a color palette for each region, making it easier to distinguish between them in the visualization. This is especially useful for categorical data, where each category (in this case, regions) is represented by a distinct color.