TDS-C01 Tableau Desktop Specialist Exam Questions and Answers

Standard deviation is an aggregation that is available without requiring a table calculation or calculated field. Standard deviation is a statistical measure that shows how much variation there is from the average value in a set of data. Standard deviation is one of the predefined aggregations in Tableau that can be applied to any measure by selecting it from the context menu of the measure or from the drop-down menu on the Marks card6 The other options are not aggregations that are available without requiring a table calculation or calculated field. Running total, sample covariance, and percent of total are all examples of table calculations, which are computations that are applied to the values in an entire table or partition of a table. Table calculations can be created by selecting them from the context menu of a measure or by using functions in a calculated field7

Yes! We get different options for filtering depending on whether we use a categorical data (think dimension) or quantitative data (think measure).

Important Note: Each tab adds additional definitions to your filter. For example, you can select to exclude values under the General tab, and also add limits under the Top tab. Selections and configurations from both tabs are applied to your filter.At any time, you can see the definitions of your filter under Summary on the General tab.

Note: If you have a large data source, filtering measures can lead to a significant degradation in performance. It is sometimes much more efficient to filter by creating a set containing the measure and then apply a filter to the set. For more information about creating sets, see Create Sets

The following options are available when an image is Exported:

NOTE: When we Copy an image rather than exporting it, then the image is copied to the clipboard in the TIFF file format! However, it is not available when EXPORTING an image.

Data blending simulates a traditional left join. The main difference between the two is when the aggregation is performed. A join combines the data and then aggregates. A blend aggregates and then combines the data.

From the official website:

According to the Tableau Help, there are two filter modes for continuous filters: Range of Values and Single Value. The help also states that “Range of Values lets you specify a minimum and maximum value for the filter using sliders or input fields” and “Single Value lets you select one value on a slider for the filter” (page 1).

When you use the 'Create Set' option in Tableau, it creates a dynamic set if the conditions for inclusion in the set are based on a calculation or an aggregation that may change as the data is updated or as filters are applied. Fixed sets are static and do not change with data refreshes, while dynamic sets can update to reflect the current state of the data.

Explanation

This is true, indeed!

The LEFT JOIN keyword returns all records from the left table (table1), and the matched records from the right table (table2). The result is NULL from the right side, if there is no match.

According to the Tableau Help, a highlight table is “a cross-tabulation that uses color to encode values”. The help also states that “Highlight tables use the Square mark type” (page 1).

Explanation

By default, all of the above mentioned are stored in Documents -> My Tableau Repository

In Tableau, when creating a combined axis chart, after dragging the first measure to the Rows shelf, you should drag the second measure directly onto the existing axis in the view. This will combine both measures on the same axis, allowing them to share a scale and an axis, which is the essence of a combined axis chart.

Before you can build a view and analyze your data, you must first connect Tableau to your data. Tableau supports connecting to a wide variety of data, stored in a variety of places.

By default, when you connect a data source to Tableau, Tableau will create a live connection to the data.

Live connection refers to a data source that contains direct connection to underlying data, which provides real-time or near real-time data. With a live connection, Tableau makes queries directly against the database or other source, and returns the results of the query for use in a workbook. Users can create live connections and then share them on Tableau Server so that other Tableau users can use the same data using the same connection and filtering settings.

You can drag the filter by clicking on the 2 lines on top, and then dragging the filter as shown:

Your Tableau Desktop Specialist exam will be based on the 2020.1 version.

Set controls are a new feature introduced in the 2020.2 version, and hence is the correct answer - it is not a part of 2020.1

For the 2020.1 version the new features were:

1) Viz animations:

Viz animations help you see and understand your changing data. It’s easy to track the logical steps behind data’s evolution and tell powerful data stories. Sorting, filtering, adding fields, and other actions will now smoothly animate your visualizations. Choose whether to turn Viz Animations on or off, and decide how you’d best like to apply animations to your new workbooks.

2) Dynamic Parameters:

Say goodbye to republishing workbooks with parameters every time the underlying data changes. Set your parameter once, and Tableau will automatically update the parameter’s list of values every time someone opens the workbook.

3) Buffer Calculations:

Buffer calculations allow you to visualize the distance around point locations. Give Tableau three parameters—location, distance, and a unit of measure—and a buffer, or boundary is instantly created. Answering complex spatial questions becomes easier than ever before—visualize what properties are within 200 meters of a proposed transit site, or how many competitors’ stores are within 1 mile of their store, and more.

Explanation

You can export the data in a Tableau data source, including all or part of the records from your original data. Alternatively, you can export only the portion of data used to generate the view.

Since the question mentions the data used to build the view, we'll focus on that :

*Export data in the view to Microsoft Access or .csv*

Export the data that is used to generate the view as an Access database (Windows only) or .csv file (Mac only).

1) In Tableau Desktop, select Worksheet > Export > Data.

2) Select a location and type a name for your Access database or .csv file.

3) Click Save.

4) If you're on Windows, the Export Data to Access dialog box displays to give you the option to immediately use the new Access database and continue working in Access without interrupting your work flow.

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A bullet graph is a variation of a bar graph developed to replace dashboard gauges and meters. A bullet graph is useful for comparing the performance of a primary measure to one or more other measures. Below is a single bullet graph showing how actual sales compared to estimated sales.

We can create a Bullet graph with just 2 measures! This method requires the LEAST number of fields possible to create this type of chart.

The best way to tackle such questions in the exam is to click the "SHOW ME" button on top right, and hover over the chart we want to create.

In our case, it is a Bullet graph.

Therefore, we need 2 measures at least to create this chart, and 0 or more dimensions.

To create a stacked bar chart in Tableau, you can drag a second dimension to the Color shelf on the Marks card. This action will segment the bars already present in the chart by the new dimension, stacking the segments on top of each other within each bar. This is a common method to add additional layers of detail to a bar chart and effectively compare parts to a whole across categories.

Important question!

Explanation

It is possible to open a Tableau support case by visiting the following link : https://www.tableau.com/support/case

Explanation

By default, all filters that you set in Tableau are computed independently. That is, each filter accesses all rows in your data source without regard to other filters. However, you can set one or more categorical filters as context filters for the view. You can think of a context filter as being an independent filter. Any other filters that you set are defined as dependent filters because they process only the data that passes through the context filter.

You may create a context filter to:

1) Improve performance – If you set a lot of filters or have a large data source, the queries can be slow. You can set one or more context filters to improve performance.

2) Create a dependent numerical or top N filter – You can set a context filter to include only the data of interest, and then set a numerical or a top N filter.

From the official documentation:

The default view that you first see in the Data Source page canvas is the logical layer of the data source. You combine data in the logical layer using relationships (or noodles).

To add totals to a view using the Analytics pane:

Also, you can add totals from the Analytics tab in the Menu above:

You can adjust the size for all charts except the Tree Map. You use dimensions to define the structure of the treemap, and measures to define the size or color of the individual rectangles. Treemaps are a relatively simple data visualization that can provide insight in a visually attractive format.

In a Tree Map, the measure itself defines the size and colour! The greater the sum of Measure for each category, the darker and larger its box.

It contains all the measures in your data, collected into a single field with continuous values - This is the definition for 'Measure Values'.

All others are True w.r.t. Measure Names!

The Measure Names field contains the names of all measures in your data, collected into a single field with discrete values.

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Documentation : https://help.tableau.com/current/pro/desktop/en-us/datafields_understanddatawindow_meavalues.htm

To display the complete list of potential data connections when connecting to a server in Tableau, you should select "More" under the "To a Server" option. This action will provide a comprehensive list of server types and data sources that Tableau can connect to.

Explanation

Whenever you add a measure to your view, an aggregation is applied to that measure by default. This default is controlled by the Aggregate Measures setting in the Analysis menu.

If you decide you want to see all of the marks in the view at the most detailed level of granularity, you can disaggregate the view. Disaggregating your data means that Tableau will display a separate mark for every data value in every row of your data source.

To disaggregate all measures in the view:

Clear the Analysis >Aggregate Measures option. If it is already selected, click Aggregate Measures once to deselect it.

When dealing with a union of two tables in Tableau, using logical tables with a single table extract is the most appropriate approach. Logical tables allow for the integration of data from multiple tables in a way that is seamless and efficient for analysis. By using a single table extract, Tableau consolidates the data from the union into one extract, optimizing performance and enabling faster data processing. This approach is particularly beneficial when working with large datasets or complex unions.

Explanation

In a box and whisker plot:

1) The ends of the box are the upper and lower quartiles, so the box spans the interquartile range

2) The median is marked by a vertical line inside the box

3) The whiskers are the two lines outside the box that extend to the highest and lowest observations.

The Shape option is available for scatter plots and packed bubbles views. The Shape option allows you to change the shape of marks in the view by selecting from a predefined set of shapes or adding custom shapes. You can access the Shape option by placing any field on Shape on the Marks card4 Scatter plots are views that show the relationship between two numerical variables by plotting them as coordinates on a Cartesian plane. You can create a scatter plot by placing at least one measure on Columns and at least one measure on Rows on the Marks card. You can then use Shape to assign different shapes to different categories or segments in your data5 Packed bubbles are views that show hierarchical data as a set of nested circles. Each circle represents a dimension member and its size is proportional to a measure value. You can create a packed bubble chart by placing one or more dimensions on Detail and one measure on Size on the Marks card. You can then use Shape to change the shape of circles to other shapes such as squares or stars6 The other options are not valid views for using the Shape option. Side-by-side circles are views that show proportions of a whole by using circles with different angles and sizes arranged horizontally or vertically. You can create a side-by-side circle chart by placing one dimension on Columns or Rows and one measure on Angle and Size on the Marks card. You cannot use Shape to change the shape of circles in this view7 Heat maps are views that show the distribution of two or more measures by using a color gradient and size. You can create a heat map by placing one or more dimensions on Columns and Rows and two measures on Color and Size on the Marks card. You cannot use Shape to change the shape of marks in this view8

Explanation

Explanation

Whenever we want to add actions to a Dashboard, we can trigger then in the following 3 ways:

1) Select

2) Hover

3) Menu

Hover is best for highlighting, select for filtering. Menu action is added to the tooltip and user can decide whether to run that action or not (best for URL actions)

Explanation

A Pareto chart is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the ascending cumulative total is represented by the line.

On the primary axis, bars are used to show the raw quantities for each dimension member, sorted in descending order.

On the secondary axis, a line graph is used to show the cumulative total in percent format.

According to Tableau's official documentation:

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In Tableau, to create a reference line, one of the axes in the view must contain an aggregated measure. Reference lines are typically used to add context or additional information to the data in a view, and they are often based on some form of aggregate such as the average, median, sum, etc., of a measure.

Dragging a continuous date value to the Rows shelf in Tableau results in a green pill on the Rows shelf, indicating a continuous field. It also results in a quantitative axis being displayed on the visualization. Continuous fields are used to create axes on charts and can represent a range of values smoothly. This is opposed to discrete date values, which would be represented by a blue pill and typically show headers or labels rather than a continuous axis.

According to the official Tableau documentation:

Dimensions don't have aggregation properties, and adding properties manually each time defeats the whole DEFAULT aggregation purpose. Window tab doesn't have any default aggregation option!

you can change the data type of a field from the Data Source tab by clicking on the drop-down menu of the field or by clicking the data type icon of the field. You cannot change the data type of a field from the Data pane or by selecting and holding the field.

This is a tricky question. We are talking about story POINTS, and not entire stories in the question.

To create a story, lets say I have a blank story with 1 dashboard and 1 worksheet.

I can simply drag the dashboard into the view to create a new story point.

Now, if I try to adjust the worksheet beside it in this same view, I cannot. See below:

The only option available is to replace the existing view. Therefore, the answer is NO since they both cannot be added.

Read more about stories in Tableau: https://help.tableau.com/current/pro/desktop/en-us/story_create.htm

Unioning is the correct answer!

From the official documentation:

For example, suppose you have the following customer purchase information stored in three tables, separated by month. The table names are "May2016" , "June2016" and "July2016."

The default behavior of Tableau when you add a measure to the view is to automatically apply an aggregation to that measure. The type of aggregation applied can vary depending on the context of the view. For example, if no other measures or dimensions affect the measure, Tableau might default to SUM. However, if there are other dimensions in the view that define the level of detail, the aggregation might be different to reflect the context.

When you double-click a continuous numeric measure named Sales in Tableau, it automatically creates a bar chart. Tableau's default behavior for a single measure is to display it as a bar chart, with the measure values represented on the Y-axis and an automatic range on the X-axis.

Explanation

Yes! To concatenate fields, they must be of same data type. However, there is a workaround which we can use - Type casting. See below:

Here, State and City are Strings, but Postal Code? Nope. It's an Integer. So we can simply use the STR() function to convert it into a String, and hence the entire equation becomes valid!

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Tables that you drag to the logical layer of the Data Source page canvas must be related to each other. When you drag additional tables to the logical layer canvas, Tableau automatically attempts to create the relationship based on existing key constraints and matching fields to define the relationship. If it can't determine the matching fields, you will need to select them.

If no constraints are detected, a Many-to-many relationship is created and referential integrity is set to Some records match. These default settings are a safe choice and provide the most a lot of flexibility for your data source.

Explanation

SUM is an aggregate function, not a table calculation!

A table calculation is a transformation you apply to the values in a visualization. Table calculations are a special type of calculated field that computes on the local data in Tableau. They are calculated based on what is currently in the visualization and do not consider any measures or dimensions that are filtered out of the visualization.

The most common Table calculations are:

Running Total

Percent Difference

Difference

Percent of Total

Rank

Percentile

These can be calculated using : Table(across), Cell, or Specific dimensions!

a calculated field that has a formula of SUM(Sales)/SUM(Profit) is a measure, because it returns a numeric value that can be aggregated and used for analysis. A parameter is a user-defined variable that can be used in calculations or filters. A dimension is a categorical field that can be used to group or slice data. A set is a subset of data based on some condition.

To set the default properties of a field to Currency in Tableau, you need to configure the number format of the field from the Data pane. This can be done by right-clicking the field in the Data pane and selecting Default Properties, then choosing the appropriate number format (in this case, Currency).

In Tableau, the two elements that can have their values changed by using a dashboard action are Sets and Parameters. Dashboard actions can be configured to modify the values within a set or a parameter, allowing for interactive and dynamic changes in the visualization based on user interactions. For example, selecting a specific data point in a dashboard can trigger an action that updates a set or changes the value of a parameter, which in turn can alter the displayed data or the appearance of visualizations within the dashboard.

Of course! As an example, see below:

1) Using the Sample Superstore data, let's plot a bar chart showing the Sales for each Category:

Observe that we have 3 marks - Each bar in a bar chart is called a mark. Similarly, each point in a scatter plot is also a mark , and so on for all charts.

1 row by 3 columns means that clearly on the y-axis (Sales), we have only a single mark - a single continous axis, but 3 different marks (Technology, Furniture and Office supplies ) on the x-axis.

2) Now let's add subcategory to the view as well (another dimension):

Observe that the number of marks has increased - i.e the number of Bars.

Also, notice we now have 1 row and 17 columns. Simply because 1 row = Sales (on the y-axis), and on the x-axis, we have 17 different columns (i.e product sub categories!!)

To update the font of an entire workbook in Tableau, you should use the "Format Workbook" pane. This feature allows you to set and modify the default font settings for the entire workbook, ensuring consistency in font style across all sheets and dashboards. It's a global setting that applies to all visual elements in the workbook, including titles, captions, axis labels, and other text elements.

Explanation

Measure names and values CANNOT be deleted in Tableau like other columns can. These are auto-generated.

Calculated Fields, and Number of records can both be deleted.

Explanation

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When creating a histogram in Tableau, bin size refers to the range of the continuous measure counted in each bin. A histogram is a chart that displays the shape of a distribution of a continuous measure. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins. The basic building blocks for a histogram are as follows: Mark type: Automatic; Rows shelf: Continuous measure (aggregated by Count or Count Distinct); Columns shelf: Bin (continuous or discrete)4 To create bins from a continuous measure, you need to specify the size of bins, which determines how many bins are created and how wide they are. The size of bins is equal to the difference between consecutive values along the axis that represents the bins. For example, if you have bins with values 0-10, 10-20, 20-30, etc., then the size of bins is 10. You can either enter a value for the size of bins manually or have Tableau suggest an optimal bin size based on a formula that considers the number of distinct rows and the minimum and maximum values in the data5 The other options are not valid definitions of bin size when creating a histogram in Tableau. The minimum number of axis ticks in the view is determined by Tableau’s automatic scaling and formatting of axes, which can be adjusted manually if needed. The count distinct (COUNTD) of items on either axis is an aggregation function that returns the number of unique values in a field, which can be used as a measure in a histogram but not as bin size. The maximum number of marks in the view is limited by the performance and readability of the visualization, which can be improved by filtering, sorting, or aggregating the data4

According to the Tableau Desktop Specialist Exam Readiness, to create a calculation that returns a customer name followed by a comma, a space, and then the customer’s age, you should use the formula [Customer Name] + “,” + STR([Age]). This is because you need to concatenate strings using the + operator, and convert the numeric field [Age] to a string using the STR() function.

According to the official documentation:

Joins are a more static way to combine data. Joins must be defined between physical tables up front, before analysis, and can’t be changed without impacting all sheets using that data source. Joined tables are always merged into a single table. As a result, sometimes joined data is missing unmatched values, or duplicates aggregated values.

Joins -

1) Are displayed with Venn diagram icons between physical tables

2) Require you to select join types and join clauses

3) Joined physical tables are merged into a single logical table with a fixed combination of data

4) May drop unmatched measure values

5) May duplicate aggregate values when fields are at different levels of detail

6) Support scenarios that require a single table of data, such as extract filters and aggregation

Explanation

Follow along:

1) Drag Assortment and Year ID (choose Discrete Month) to Columns shelf, and Sales to the Columns Shelf.

For sales, click on the pill -> choose Quick Table calculation ->  Year over Year growth.

The view should now look like:

Explanation

Follow along the steps below:

• Drag Assortment and Year ID to the column shelf, and Item Number ID to the row shelf. Next, drag Sales to the Text label to create a cross-tab as below:

*Very important question*

If we select the labels in the view and then group, a new consolidated mark is created - in our case bar since we are talking about a bar chart in the question. See below:

Then on grouping, a new bar is created, and the colour of all bars remain the same.

Had we grouped by choosing the marks instead of the labels, the following would be the result:

For Standard Deviation and Variance, we don't need to use quick table calculations, since they are available by default. See below:

However, as seen in the types of quick table calculations available in Tableau, Rank and Moving Average belong to only this category.

Date values in Tableau represent specific points in time and are typically formatted in a standard date format.

• Option A, "2020-05-01", is a standard date format representing the 1st of May, 2020.
• Option D, "January 1, 1995", is another example of a date value, representing the 1st of January, 1995. Options B ("December") and C ("Wednesday") represent a month and a day of the week, respectively, but do not specify a particular date.

Since Sales is a measure, it can easily be depicted via size.

To drill down and change the level of detail, Country is the correct choice since it will contain STATE. We can then depict the various states by different shapes such as circle, square etc.

Finally, the Profit can be depicted via a color! Eg - Red for poor and green for excellent profits!

Names and Categories would be mostly used as dimensions (categorical data).

Profit and measures contain quantitative data and would be more suitable for Measures!

Data blending is performed on a sheet-by-sheet basis and is established when a field from a second data source is used in the view. To create a blend in a workbook already connected to at least two data sources, bring a field from one data source to the sheet—it becomes the primary data source.

Switch to the other data source and use a field on the same sheet—it becomes a secondary data source. An orange linking icon will appear in the data pane, indicating which field(s) are being used to blend the data sources.

According to the official Tableau Documentation:

To read more about Data Blending, click on THIS link.

Explanation

Follow along to get the correct answer:

• Drag Country to the view, and then Patents to the Size Mark on the Marks shelf as follows :

2) But, this isn't all right? We need to focus on the year 2013. This can be done by using the year column as it is (continuous) in the filter shelf, or by converting it to discrete first and then using it:

2.1 As it is (continuous)

2.2 Converting to discrete first & then using it

and then :

3) We can now see that France, with 485 has the 2nd most number of patents for the year 2013

The only incorrect option is - Click on Dashboard in the Menu bar, select Tooltip, and then use the italics option.

This option doesn't exist. See below:

The rest of the options do exist, and therefore are correct:

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The option to create bins in Tableau is available for numeric fields. Bins allow you to group a series of numeric values into larger segments, which can simplify analysis and help in creating histograms or other visualizations that show the distribution of data. For example, you can create bins to group ages into categories like 0-10, 11-20, etc.

Explanation

The different aggregations available for a measure determine how the individual values are collected: they can be added (SUM), averaged (AVG), or set to the maximum (MAX) or minimum (MIN) value from the individual row values.

For a complete list of the available aggregations, check out - List of Predefined Aggregations in Tableau.

The level of detail is determined by the dimensions in your view—for information about the concept of level of detail, see How dimensions affect the level of detail in the view.

Disaggregating your data can be useful for analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.

Disaggregating data can be useful when you are viewing data as a scatter plot. See Example: Scatter Plots, Aggregation, and Granularity.

Explanation

The following is the official documentation for the String function LEFT:

For a scatter plot view in Tableau, you can add reference lines and trend lines as part of the analytics options. Reference lines can be added to a visualization to mark certain values or to provide context, such as an average line across a scatter plot. Trend lines, on the other hand, are used to show the relationship between two variables in the view, indicating the general direction or pattern of the data points in a scatter plot.

After creating a dual axis chart, make sure to synchronise their axis since they both might not be having the same y-axis.

To align the two axes in a dual axes chart to use the same scale, right-click (control-click on Mac) the secondary axis, and select Synchronize Axis. This aligns the scale of the secondary axis to the scale of the primary axis.

In this example, the Sales axis is the secondary axis and the Profit axis is the primary axis.

If you would like to change which axis is the primary, and which axis is the secondary, select the field on the Columns or Rows shelf that is the secondary, and drag it in front of the primary field on the shelf until you see an orange triangle appear.

In this example, you can select the SUM(Sales) field on the Rows shelf, and drag it in front of the SUM(Profit) field. The Sales axis is now the primary and the Profit axis is the secondary.

According to the official Tableau documentation:

You should change the mark type of the view to configure the visualization as a density map. A density map is a type of mark that shows how data points are distributed in a two-dimensional space. To change the mark type, you can use the Marks card or Show Me. Changing the mark shape, creating a custom color palette, or selecting heat maps from Show Me will not create a density map2

Explanation

Joins combine tables by adding more columns of data across similar row structures. This can cause data loss or duplication if tables are at different levels of detail, and joined data sources must be fixed before analysis can begin.

Inner join

Left Join

Blends, unlike relationships or joins, never truly combine the data. Instead, blends query each data source independently, the results are aggregated to the appropriate level, then the results are presented visually together in the view.

Explanation

When using a Percent difference, Tableau calculates what the percent change has occured as compared to the last data value. BUT, for the first data value, there is no previous value to compare it to. Hence, it appears as NULL.

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Explanation

Tableau Data Extract (TDE) is a snapshot of the data that Tableau stores locally. Good for very large datasets of which we only need few fields. Performance is optimised because it queries its own database engine instead of the local data source.

When you create an extract of your data, you can reduce the total amount of data by using filters and configuring other limits. After you create an extract, you can refresh it with data from the original data. When refreshing the data, you have the option to either do a full refresh, which replaces all of the contents in the extract, or you can do an incremental refresh, which only adds rows that are new since the previous refresh.

Extracts are advantageous for several reasons:

1) Supports large data sets: You can create extracts that contain billions of rows of data.

2) Fast to create: If you're working with large data sets, creating and working with extracts can be faster than working with the original data.

3) Help improve performance: When you interact with views that use extract data sources, you generally experience better performance than when interacting with views based on connections to the original data.

4) Support additional functionality: Extracts allow you to take advantage of Tableau functionality that's not available or supported by the original data, such as the ability to compute Count Distinct.

5) Provide offline access to your data: Extracts allow you to save and work with the data locally when the original data is not available. For example, when you are traveling.

You should use a union when you have two tables with similarly named columns of data that you want to combine. A union is a method for combining data by appending rows of one table onto another table. The tables that you union must have the same number of fields, the same field names, and the same data types2

Explanation

THIS IS A VERY IMPORTANT QUESTION

To answer this question, you need to understand Tableau's Order of Operations. See below and remember this always:

Explanation

Phew! Tricky one for sure. This question tests multiple concepts and will help you revise them. We'll be using filters, as well as quick table calculations (percent of total) for this one.

1) Firstly, let's drag Country and Institution to the Rows shelf, and year (discrete) to the Columns shelf. Then, drag Publications to the Text Icon in the Marks Shelf. The following is our view:

To make an axis bold, simply right click it, select format, and then click on Font to choose Bold:

None of the other options are valid ways to make the axis bold.

Read more about editing axis: https://help.tableau.com/current/pro/desktop/en-us/formatting_editaxes.htm

Explanation

Tricky options! Go to hyperlink and Go to Web page are not valid Actions in Tableau.

A URL action is a hyperlink that points to a web page, file, or other web-based resource outside of Tableau. You can use URL actions to create an email or link to additional information about your data. To customize links based on your data, you can automatically enter field values as parameters in URLs.

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Explanation

As the names suggest, if we subtract the order date from the shipping date, we simply get the number of days between these 2 dates.

We can these use this calculated field in our charts, and can use COUNT, SUM, AVG etc with them according to our need.

In Tableau, parameters are dynamic values that can replace a constant in calculations, filters, and reference lines. If you have a parameter controlling a calculation, changing the parameter value can change the results of that calculation, thus impacting the visualization. Parameters can also be used to switch between different fields in the visualization; for example, allowing users to choose which measure or dimension to display.

According to the Tableau Desktop Specialist Exam Guide, a packaged workbook (.twbx) includes background images, extract files, and custom shapes. A PDF copy of the workbook and Tableau Datasource Customization (TDC) files are not included in a packaged workbook.

Upon clicking on a filter, we see the following options:

Clearly, Regex Match is not one of these options!

Explanation

Tableau Public is a free service that lets anyone publish interactive data visualizations to the web. Visualizations that have been published to Tableau Public (“vizzes”) can be embedded into web pages and blogs, they can be shared via social media or email, and they can be made available for download to other users.

Check it out : https://public.tableau.com/en-us/s/

According to the official Tableau documentation:

Tableau packaged workbooks have the .twbx file extension. A packaged workbook is a single zip file that contains a workbook along with any supporting local file data and background images. This format is the best way to package your work for sharing with others who don’t have access to the original data. For more information, see Packaged Workbooks.

You can use Wildcard Search to set up search criteria to automatically include tables in your union. Use the wildcard character, which is an asterisk (*), to match a sequence or pattern of characters in the Excel workbook and worksheet names, Google Sheets workbook and worksheet names, text file names, JSON file names, .pdf file names, and database table names.

When working with Excel, text file data, JSON file, .pdf file data, you can also use this method to union files across folders, and worksheets across workbooks. Search is scoped to the selected connection. The connection and the tables available in a connection are shown on the left pane of the Data source page.

To create a packaged data source (.tdsx file) in Tableau, you would right-click on the data connection in the Data pane and select the option to add it to saved data sources. This action packages the data source with the metadata that you've defined in Tableau, such as calculations, groups, and sets, so that you can easily share it with others. This does not package the data itself, which is a separate step if you're working with local file-based data.

You can use a story to present a data narrative to lead your audience to your conclusions, or to assemble a sequenced analysis to share with collaborators. A story is a sequence of visualizations that work together to convey information. You can create stories to tell a data story, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case4

According to the Tableau Desktop Specialist Exam Guide, one of the exam objectives is to “Sort data in a visualization”. The guide also states that “You can sort data in a visualization from three locations: the Worksheet menu, an axis, or a field label” (page 15).

The only incorrect option is - It is mandatory to combine sheets when using Tableau.

All others are valid advantages that Dashboards provide when using Tableau!

To change a measure so that it automatically aggregates as an average instead of a sum, you should right-click the field in the Data pane and select Default Properties. In the Default Properties menu, you can set the default aggregation for the measure, such as setting it to calculate an average by default when added to a view.

To create a simple scatter plot in Tableau, you need to have a measure on Columns and a measure on Rows. A scatter plot is a type of visualization that shows the relationship between two numerical variables. In Tableau, you can create a scatter plot by placing at least one measure on the Columns shelf and at least one measure on the Rows shelf. The measures can be continuous or discrete, but they must be aggregated. The marks in the scatter plot represent the intersection of the values for each measure1 The other options are not valid ways to create a simple scatter plot in Tableau. A dimension on Detail and a measure on Columns will create a bar chart, not a scatter plot. A dimension on Columns and a measure on Rows will create a line chart or an area chart, depending on the mark type. A dimension on Columns and a dimension on Rows will create a text table or a heat map, depending on the mark type1