Tableau Desktop Specialist Exam Dumps & Questions 2025
Tableau Desktop Specialist Exam Dumps & Questions 2025
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Question 1:
Which of the following is true for relationships?
A. We cannot edit the relationship after publishing.
B. We cannot create Relationship on the calculated field.
C. We can create relationships using date field.
D. Relationship give us the different options for join type.
Answer: C
Explanation:
We cannot edit the relationship after publishing. This is incorrect. While it’s generally recommended to test relationships thoroughly before publishing, you can edit them after publishing if necessary.
We cannot create Relationship on the calculated field. This is incorrect. You can create relationships using calculated fields as long as they have a data type that can be used in relationships (e.g., text, number, date).
Relationship give us the different options for join type. This is incorrect. While relationships do provide different join types (e.g., inner join, outer join), these are typically used in database queries rather than within the relationship definition itself.
Therefore, the only true statement is that you can create relationships using date fields.
Question 2:
How stacked bar charts are helpful
A. How data change over time.
B. We use stacked bar charts when we want to visualize parts of a whole.
C. With this chart, we are able to visualize complex information in a few marks.
D. Find the cumulative analysis.
Answer: B
Explanation:
We use stacked bar charts when we want to visualize parts of a whole.
Stacked bar charts are particularly useful for:
Comparing parts of a whole: Each bar represents a whole, and the different colored segments within the bar represent the different parts that make up that whole.
Tracking changes over time: Stacked bar charts can be used to show how the composition of a whole changes over time.
Identifying trends: By comparing the size of different segments across bars, you can identify trends and patterns in the data.
However, stacked bar charts can become difficult to interpret when there are many segments or when the segments are very similar in size. In such cases, other chart types, such as grouped bar charts or pie charts, may be more suitable.
Question 3:
Forecasting is always plotted on the continuous date field.
A. TRUE
B. FALSE
Answer: A
Explanation:
Step-by-Step Guide to Creating a Forecast in Tableau
Connect to Your Data:
Start by connecting to your data source in Tableau Desktop.
Prepare Your Data:
Ensure that your data includes a time dimension and the measure you want to forecast.
The time dimension should be in a format that Tableau recognizes as a date or time.
Create a Visualization:
Drag and drop the time dimension onto the Columns or Rows shelf.
Drag and drop the measure you want to forecast onto the Columns or Rows shelf as well.
This will create a basic visualization.
Enable the Forecasting Feature:
Right-click on the measure in the visualization and select "Forecast" from the context menu.
Tableau will analyze the data and apply a default forecast model.
Adjust the Forecast Settings:
Right-click on the forecast line or click on the forecast card in the Marks card to access the forecast options.
Change the forecast length, confidence interval, and other settings based on your requirements.
Customize the Visualization:
Format and customize the forecast visualization by changing the chart type, adding additional fields or dimensions, and applying desired formatting options.
Question 4:
Which of the following is true about table calculation?
A. Table calculation can be implemented on the measures.
B. Addressing and partitioning options are available.
C. Table calculation depends on the table structure.
D. Table calculation are occurs at data source page level.
Answer: A, B and C
Explanation:
Table Calculations in Tableau
Table calculations in Tableau are computations performed on the results of a query or data set within a visualization. They allow you to perform calculations that go beyond simple aggregations or calculations based on individual rows or columns. Table calculations operate on a set of values within a specific scope, such as a partition or a table, and can produce dynamic results that change based on the dimensions and filters applied to the visualization.
Key Concepts:
Scope: Table calculations can be applied at different levels of granularity, such as at the level of individual rows, specific dimensions, or partitions within the data. You can define the scope by selecting the appropriate dimensions and fields.
Calculation Types: Tableau provides various built-in table calculation functions to perform computations, including running totals, percent of total, moving averages, rank, difference from previous or next value, and many more. You can choose the desired calculation type based on your analysis requirements.
Compute Using: Table calculations can be computed using different dimensions or levels of detail in your visualization. The "Compute Using" option in Tableau allows you to specify the dimensions or fields that define the calculation's scope.
Aggregation and Partitioning: Table calculations can be performed within a partition, which is a subset of data defined by one or more dimensions. You can specify the partitioning options to control how calculations are computed within each partition.
Order of Operations: Table calculations are computed after the data is aggregated, allowing you to perform calculations on summarized results. However, the order of operations can be adjusted using the Tableau's "Edit Table Calculation" dialog box to specify the order in which calculations are computed.
Question 5:
Which of the following is true about dimension and measure?
A. State name, customer name etc. comes under dimension and numeric type field comes under measure.
B. Same data type can be concatenate.
C. We can compare string with float.
D. Dimension are independent variable and measure are dependent variable.
Answer: A, B and D
Explanation:
Dimension:
* Represents qualitative, categorical, or descriptive data.
* Defines the categorical aspects of your data, such as names, categories, or labels.
* Typically contains discrete, non-numeric data.
* Used for grouping, filtering, and organizing data in visualizations.
* Not aggregated by default.
* Represents individual, discrete values that are used for categorization and organization.
* When added to a visualization, Tableau treats each unique value as a separate entity or category.
Measure:
* Represents quantitative, numeric, or continuous data.
* Defines the measurable aspects of your data, such as quantities, amounts, or numerical values.
* Typically contains numerical data that can be aggregated, summarized, and used in mathematical calculations.
* Inherently aggregatable.
* Represents numeric values that can be aggregated using various mathematical functions such as sum, average, count, min, max, and so on.
* Can be used to perform calculations and produce aggregated results based on the dimensions used in the visualization.
For a full set of 1020 questions. Go to
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SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
SkillCertPro updates exam questions every 2 weeks.
You will get life time access and life time free updates
SkillCertPro assures 100% pass guarantee in first attempt.
Question 6:
Why do we use a line chart for our analysis?
A. Activity over a period of time is represented.
B. Comparison analysis.
C. Time series analysis.
D. Contribution analysis.
Answer: A and C
Explanation:
Line charts are useful for understanding trends, patterns, and changes in values over time or other continuous dimensions.
1. Trend analysis: Line charts are mostly used to analyze trends and patterns in our data. By visualizing the data points that are connected by continuous lines, we can easily identify the direction in which our observed data changes over time or in other continuous dimensions. By doing so, we can easily determine if our data is increasing, decreasing, or remaining relatively stable as per the time period.
2. Time series analysis: These charts are commonly used to analyze time-series data and also allow us to identify how data changes over time, seasonal patterns, long-term trends, or short-term variation. Time-series line charts are useful in different domains such as stock market trend analysis, sales analysis, weather pattern change, and more.
3. Comparisons and Relationships: It can be used to compare multiple data variables simultaneously. By plotting multiple lines for different measures on the same pane of chart, we can compare the trends and relationships between different variables. It also helps to find the correlations, outliers, and divergences among the values.
Question 7:
Making hierarchy obsolete
A. It is possible to remove hierarchy from measure only
B. Go to hierarchy -> mouse right button-> remove hierarchy
C. Worksheet -> remove hierarchy
D. We can’t remove hierarchy once created.
Answer: B
Explanation:
It helps you explore and analyze your data at different levels of granularity. For example, you can have a hierarchy with dimensions like:
Year
Quarter
Month
Day
This allows you to easily navigate and analyze your data at different time intervals.
Hierarchies enable you to do drill-down analysis, allowing you to progressively explore data in a more detailed manner. You can dive deeper into the data and gain insights at a more granular level by using levels of the hierarchy.
It provides a way to simplify visualizations by reducing the number of dimensions displayed at once. Instead of showing multiple dimensions individually, you can use hierarchies to consolidate related dimensions into a single field in the view, resulting in cleaner and more focused visualizations for your analysis.
Question 8:
How a live connection is represented?
A. Single cylinder
B. Double cylinder
C. Vane
D. Paper clip
Answer: A
Explanation:
Live Connections in Tableau
In Tableau, a live connection is a type of data connection that allows you to connect directly to a data source while working. When you create a live connection, Tableau establishes a connection to the data source and retrieves the data dynamically as you interact with the visualization.
Key Points:
Real-time Data: Once connected live, Tableau fetches data directly from the data source and displays it in the data source tab.
Dynamic Updates: Any changes made to the data source are reflected in Tableau immediately.
Performance Considerations: Live connections can be slower for large data sources or slow network connections.
Analogy: Single Cylinder
In this analogy, a "single cylinder" represents a live connection, indicating a direct and real-time connection to the data source. With a live connection, Tableau queries the data source on-the-fly to retrieve and display the data in real-time as you interact with the visualization.
Extract Connections in Tableau
On the other hand, an "extract" is represented by a "double cylinder" in this analogy. An extract connection involves creating a local snapshot of the data source within Tableau. It is referred to as an extract, allows for faster performance, and can be accessed offline. When you work on an extract connection, Tableau retrieves and stores a subset of the data in the extract file, which can be refreshed periodically to get the updated data.
Question 9:
Which table calculation do we use to find the percentage difference as compared to the previous year?
A. Difference
B. Running total
C. Rank
D. Percentage difference
Answer: D
Explanation:
Percentage Difference in Tableau
Percentage difference is a quick table calculation in Tableau used to compare the current year with the previous year.
Understanding Percentage Difference:
A percentage difference, also known as a percent difference or relative difference, is a calculation used to measure the percentage change between two values or quantities. It is commonly used to compare the difference or change between two numbers in terms of their relative magnitude.
Calculating Percentage Difference:
Determine the two values: Value 1 and Value 2.
Calculate the difference: Difference = Value2 - Value1.
Calculate the percentage difference: Percentage Difference = (Difference / |Value1|) * 100
Example:
Value 1 = 50
Value 2 = 70
Difference = 70 - 50 = 20
Percentage Difference = (20 / |50|) * 100 = 40%
In this case, Value 2 is 40% higher than Value 1.
Question 10:
Why should we prefer extract connection over the live one?
A. It will query the date from the Tableau data engine.
B. Extracting takes more time.
C. Less performance for large data sources.
D. The query execution time is less.
Answer: A and D
Explanation:
Extract Connections in Tableau
An extract connection in Tableau works based on a snapshot of the data source, eliminating the need for a live connection to the data source itself. This results in faster query execution times as there is no dependency on the live data source during analysis.
Key Advantages:
Improved Performance: Extract connections provide better performance compared to live connections because the data is already extracted and stored locally, allowing for faster data retrieval and analysis. The extracted data is optimized for Tableau's querying and visualization capabilities.
Offline Access: One of the significant advantages of using an extract connection is the ability to work with the data from anywhere and at any time, even without an internet connection. Since the data is stored locally in the extract file, you can access and analyze it offline, providing flexibility and convenience.
In summary, an extract connection offers improved performance, faster query execution, and the flexibility to work offline without the need for a live connection to the data source.
For a full set of 1020 questions. Go to
https://skillcertpro.com/product/tableau-desktop-specialist-exam-questions/
SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
SkillCertPro updates exam questions every 2 weeks.
You will get life time access and life time free updates
SkillCertPro assures 100% pass guarantee in first attempt.