This is one of the most common questions on the Tableau Desktop Specialist Exam.

Wrong options -

1) Don't use backgrounds - This is not a solution. What if we want to use backgrounds? We can't just stop using backgrounds to solve this problem.

2) Decrease the font size - Do you think using a smaller font will make the text more readable? No right? Hence, this is wrong too.

All other options are ways recommended to make your text more readable!

Yes, due to the nature of blends, there are some conditions as follows from the official documentation that must be kept in mind while working with blends:

In addition to handling calculations slightly differently, there are some limitations on secondary data sources. You may not be able to sort by a field from a secondary data source, and action filters may not work as expected with blended data. For more information, see Other data blending issues.

To create a trend line, we need:

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

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!

Explanation

If you chose 111,060 you were SO close to the correct answer but made a small mistake - you didn't change the aggregation to AVERAGE! This is one of the common mistakes many test takers make, so keep this in mind.

To reach the correct answer, follow the steps below:

1) Draw Assortment to the Column shelf, and drag Year to the Rows Shelf. Then Drill down further on Year to accomodate Quarters and Months as well!

Although this seems enough, DON'T FORGET to change the aggregation like in the next step, which will completely change the values!

The correct answer as you can see is 1,461 - Sales for Harware Assortment in 2017 Q4, October

Explanation

Tableau recognises a CSV file as a TEXT file, and therefore it is the correct option.

The following are the steps to import a CSV file:

1) From the data connection screen, click on Text:

2) Choose the appropriate file, and click Open:

3) Finally, Tableau imports the data as shown below:

The relative date filter can be used to select a range of dates relative to the current date, such as the past month, the current quarter, etc. This filter type dynamically adjusts the range based on the current system date, making it suitable for use with the TODAY() function.

Explanation

We can perform filter, URL and highlight actions out of the above given choices on a dashboard. Please refer to the image below:

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.

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.

Only 1 option is correct -

Click on Dashboard in the Menu bar followed by Copy Image

Right click on the dashboard, and choose Copy, then image - Try doing this, you will end up copying just one of the worksheets not the entire dashboard

Click on Worksheet in the Menu bar followed by Export, then choose Image - Again, try doing this. You will end up copying just one of the worksheets not the entire dashboard

Using the floating export worksheet option on the Dashboard - No such option exists

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.

Explanation

You can create a group to combine related members in a field. The icon associated with a group is a paper clip!

Explanation

The INNER JOIN keyword selects all rows from both tables as long as there is a match between the columns. Consider 2 tables "Orders" and "Customers".

If there are records in the "Orders" table that do not have matches in "Customers", these orders will not be shown!

 You can share a dashboard as an image file by using one of the following methods: Export Image on the Dashboard menu, or a dashboard export button. Export Image on the Dashboard menu allows you to export the dashboard as an image file in BMP, JPEG, PNG, or SVG format. A dashboard export button is a custom button that you can create on your dashboard to export it as an image file using a URL action

To visually group marks in Tableau, you typically start by selecting the marks directly in the view. Once the desired marks are selected, you can then create a group from them. This will visually group the selected marks, as indicated by the blue color in the example provided.

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.

Using the Sample superstore as a reference:

1) Let's plot a bar chart showing SUM(Quantity) for each Segment:

2) Right click on the x-axis (Segment):

Notice we don't have an option to edit the axis, only header. This is because only continous values form the AXIS.

3) Similarly, right click on the y-axis (Quantity):

Now we have the option to edit BOTH the axis and the header.

Explanation

When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains. You use these fields to build views of your data.

Explanation

Relative date filters dynamically update to show a time period relative to when you open the view, such as the current week, the year to date, or the past 10 days. Relative date filters make it easy to create views that always show the most recent data.

Step 1: Drag a date field to the filter shelf

Right-click (control-click on Mac) and drag a date field from the Data window to the Filters shelf. In the Filter Field dialog box, click Relative Date, and then click Next.

Step 2: Select a time unit

In the Filter dialog box, click Relative dates, and then select the unit of time for the filter. For example, to show only the three most recent weeks, select Weeks.

Here, you can clearly see that the default date is TODAY

Top of Form

To clean and automatically fix the data issues in our data source - This is the definition of Data Interpreter.

To rename the field in the original data source - We never modify the original data source when managing metadata. All changes are local to Tableau for our convenience only.

All other options can be modified using the Manage Metadata property.

Bottom of Form

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.

Explanation

It is possible to join a maximum of 32 tables in Tableau!

When creating a date filter in Tableau, anchor refers to the date in a relative-date filter to which you anchor a unit of time. A relative-date filter is a type of filter that allows you to dynamically filter data based on a range of time relative to the current date or a specific date. For example, you can use a relative-date filter to show data for the last 7 days, the next 3 months, or the current quarter1 To create a relative-date filter, you need to specify the following options: The date field that you want to filter. The unit of time that you want to use for the filter, such as days, weeks, months, quarters, or years. The range of time that you want to show relative to the anchor date, such as last, next, this, or to date. The anchor date that you want to use as the reference point for the filter. You can use the current date or a custom date as the anchor date1 For example, if you want to create a relative-date filter that shows data for the last 3 months from January 1st, 2022, you would select the following options: Date field: Order Date Unit of time: Months Range of time: Last 3 Anchor date: Custom (01/01/2022) 1 The other options are not valid definitions of anchor when creating a date filter in Tableau. The mid-point in the range of displayed dates is not related to the anchor date, but rather to the center of the axis that represents the date field. The date in a range-of-dates filter to which you anchor units of time is not correct, because a range-of-dates filter does not use an anchor date, but rather a start and end date that can be fixed or dynamic. The latest date in the data source that can be found is not related to the anchor date, but rather to the maximum value of the date field in the data source2

Explanation

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

This is a tricky question often asked in the exam.

If we drag a new measure to the row shelf, the following happens:

We now have 2 rows, and the same 7 columns for both these rows. Therefore, 2x7 = 14 marks!

But if we drag the same measure to the column shelf, we have just 1 row and a chart created for each of the columns. So (1x7) = 7 marks!

Reference and notes: https://medium.com/@justindixon91/tableau-specialist-exam-notes-part-4-understanding-tableau-concepts-f78de83fdd35

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

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.

Distribution Pane

Explanation

This is the Analytics pane! Read more from the official documentation below:

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.

Explanation

Pretty common question on the Tableau Desktop Specialist exam.

1) First, lets create Sheet 1. For this, drag sport to the Row shelf, and Weight to the Text mark in the Marks shelf. Change its aggregation to Average:

2) Now, for sheet 2 - Drag nationality to the view, and gold to the size mark in the Marks shelf.

NOTE: Depending on your version of Tableau , you may need to assign a Geographical role to the nationality column first as follows:

3) Now, let's create a dashboard, and use both these sheets in it:

4) Now, for the most Important step, use SHEET 2 AS A FILTER FOR SHEET 1 as follows:

Now simply click on Russia in Sheet 2, and Sheet 1 will automatically update as follows:

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.

The beauty of context filters is that according to Tableau's Order of Operations, they are executed before Sets.

This means that based on what Region's you've selected - Tableau will first only preserve the rows for those Regions. THEN, after this it will compute the Set , i.e , Bottom 10 products in each Region.

1) First let's create a set to compute the Bottom 10 Products by Profit.

2) Next, take region on the Rows Shelf followed by the Set we just created. Drag Region and the Set to the Filters Shelf as well.

3) Now, try to only visualize the data for the South Region:

4) The problem right now is that Tableau is computing the Set first (Bottom 10 Products), and then applying the Dimension Filter - South Region and hence these values are incorrect. Note how these aren't even 10 products, but rather just 8. To fix this, simply add Region to Context:

Upon doing this, we get the correct answer as : 

References: https://help.tableau.com/current/pro/desktop/en-us/order_of_operations.htm

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

Explanation

GDP / Population = GDP Per Capita

Here Sum is a function, / and + are operators. On the bottom there are comments.

Discrete measures and discrete dimensions appear blue in Tableau. Discrete fields are those that have a finite number of distinct values, such as names, categories, or dates. Discrete fields are usually used to create headers or labels in the view. Blue fields indicate that the field is discrete. Continuous measures and continuous dimensions appear green in Tableau. Continuous fields are those that have an infinite range of possible values, such as numbers or ratios. Continuous fields are usually used to create axes or color gradients in the view. Green fields indicate that the field is continuous1

Explanation

When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains. You use these fields to build views of your data.

Exporting the visualisation gives us a static view of the visualisation.

It is NOT possible to interact with it, use filters, or dynamically enter anything in a visualisation exported PDF.

In Tableau Desktop, you can save views as PDF files rather than printing them as hard copies. You do not need to have Adobe Acrobat installed on your computer.

When you print an individual sheet to PDF, filters in the view are not included. To show filters, create a dashboard containing the sheet and export the dashboard to PDF. (IMPORTANT)

By default, the shape that a Heap map uses is a "Square". See below:

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.

By default, measures placed in a view are aggregated. Mostly you'll notice that the aggregation is SUM, but not ALWAYS.

The type of aggregation applied varies depending on the context of the view.

To add totals to a view using the Analytics pane:

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

Explanation

We can very much blend multiple measures into a single axis. Such charts are called Combined-Axis / Blended-Axis charts. Follow along:

Measures can share a single axis so that all the marks are shown in a single pane. To blend multiple measures, drag one measure or axis and drop it onto an existing axis.

Instead of adding rows and columns to the view, when you blend measures there is a single row or column and all of the values for each measure is shown along one continuous axis. For example, the view below shows quarterly sales and profit on a shared axis.

Note: If you drag a measure on to the canvas and only see a single ruler indicator instead of the double ruler indicator shown below, Tableau creates dual axes instead of a blended axis. For more information about how to create dual axes, see Compare two measures using dual axes.

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.

All answers except November are examples of Date Values (continuous in nature).

See below:

You can see that the option in Green symbolizes our correct answer, i.e only a Month. In our case that month is November (the correct answer).

All other options are combinations of a year with one other value (like a month, quarter, or day). So this is how by looking at an option you can know if its a date part or date value!

Three statements that accurately describe dimensions are: Contain qualitative values Affect the level of detail in the view Can be continuous or discrete Dimensions are fields that contain qualitative values, such as names, dates, or geographical data. You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view by creating headers or labels for marks or by defining how data is partitioned for table calculations. Dimensions can be continuous or discrete depending on their data type and format. Continuous dimensions are those that have an infinite range of possible values, such as numbers or ratios. Discrete dimensions are those that have a finite number of distinct values, such as names, categories, or dates3 The other options are not accurate statements about dimensions. Contain numeric, quantitative values is not correct, because fields that contain numeric, quantitative values are measures, not dimensions. Measures are fields that contain numeric values that you can measure and aggregate. Affect the formatting options in the view is not correct, because formatting options are not determined by dimensions, but rather by user preferences and choices. Formatting options allow you to change the appearance of various elements in the workbook, such as fonts, borders, shading, alignment, etc3

To show how Internet Usage values change from year to year as a percentage, you should apply the "Percent Difference" quick table calculation to the Internet Usage field. This calculation compares each value to the previous value and computes the difference as a percentage, which is ideal for analyzing the rate of change over a sequential time period such as consecutive years.

Explanation

If you chose 2, then you were very close but probably didn't plot the actual Percent Difference on your view. ( One of the marks is just over the line).

Firstly, Drop the Week ID onto the column shelf, and convert it to continuous since we need both Year and Quarter as mentioned in the question.

2) Next, Drop assortment to filters shelf so that we can focus on Electronics!

3) This should be your view now. Click on the Show Mark Labels icon as shown:

The final view is as follows, with 3 points below 0 ( i.e negative )

According to Tableau's official documentation:

Explanation

A geographic role associates each value in a field with a latitude and longitude value.

Assigning a geographic role based on the type of location (such as state versus postcode) helps ensure that your data is plotted correctly on your map view. For example, you can assign the City geographic role to a field that contains a list of city names.

To assign a geographic role to a field:

In the Data pane, click the data type icon next to the field, select Geographic Role, and then select the geographic role you want to assign to the field.

When you assign a geographic role to a field, Tableau adds two fields to the Measures area of the Data pane: Latitude (generated) and Longitude (generated).

These fields contain latitude and longitude values and are assigned the Latitude and Longitude geographic roles. If you double-click each of these fields, Tableau adds them to the Columns and Rows shelves and creates a map view using the Tableau background map.

Explanation

This question is directly from the Official Tableau Desktop Specialist exam guide.

Since we are talking about the AVERAGE home values for the United States in 2016, the question is directly offering us a hint that the answer has something to do with aggregation and that too the values tell us that we're working with MEASURES.

Date part and Date values don't really make much sense given the question, and neither does geography.

Therefore, the answer naturally is "An aggregated measure".

The Tableau workspace consists of menus, a toolbar, the Data pane, cards and shelves, and one or more sheets. Sheets can be worksheets, dashboards, or stories. For details on dashboard or story workspaces, see Create a Dashboard or The Story Workspace.

Graphical user interface, application Description automatically generated

The main thing you do in the workspace is to create visualisations to analyze your data.

Renaming data fields, cleaning the data, previewing the data can all be done in the Data source window.

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

Explanation

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.

To work with the MOST up-do-date data, use a live connection instead!

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 (Option stating - To create a dependent filter eliminated here). 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.

For example, suppose you’re in charge of breakfast products for a large grocery chain. Your task is to find the top 10 breakfast products by profitability for all stores. If the data source is very large, you can set a context filter to include only breakfast products. Then you can create a top 10 filter by profit as a dependent filter, which would process only the data that passes through the context filter.

A parameter is a global placeholder value such as a number, date, or string that can replace a constant value in a calculation, filter, or reference line.

For example, you may create a calculated field that returns True if Sales is greater than $500,000 and otherwise returns False. You can replace the constant value of “500000” in the formula with a parameter. Then, using the parameter control, you can dynamically change the threshold in your calculation.

For example -

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.

Explanation

We can drag fields from the Data pane to create the structure for your visualizations.

The Columns shelf creates the columns of a table, while the Rows shelf creates the rows of a table. You can place any number of fields on these shelves.

These FIELDS are also referred to as PILLS. See below:

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

There are two types of sets: dynamic sets and fixed sets. The members of a dynamic set change when the underlying data changes. Dynamic sets can only be based on a single dimension.

To create a dynamic set:

1) In the Data pane, right-click a dimension and select Create > Set.

2) In the Create Set dialog box, configure your set. You can configure your set using the following tabs:

General: Use the General tab to select one or more values that will be considered when computing the set.

You can alternatively select the Use all option to always consider all members even when new members are added or removed.

None of the other options exist, and therefore are incorrect answers.

1) Right click on Rows or Columns, and choose format. In the Font option click on Bold. (CORRECT) - this will modify only the selected axis (row or column)

2) Choose Format then Font from the Menu bar, and select Bold under the Header option (INCORRECT) - this modifies both rows and columns at the same time

3) Choose Format from the Menu bar, select Row or Column, and then select Bold under the header option (CORRECT) -  this will modify only the selected axis (row or column)

4) Select Text Label on the Marks Card, choose Rows or Columns, and then select Bold. (INCORRECT) - no such option exists

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.

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.

Dashboard actions in Tableau are interactive elements that can be used to create a more dynamic experience. These actions can be set to filter data on the dashboard, highlight specific elements, or even direct the user to a URL when interacting with a visualization. They can be triggered by user interaction such as hover, selection, or accessing a context menu. Moreover, dashboard actions can have multiple source sheets (where the action originates) and target sheets (where the action takes effect), allowing for a complex interactivity between different parts of the dashboard.

Explanation

Yes! It is possible to duplicate a field and add it to more than one hierarchy. Right click and choose duplicate.

According to the [Tableau Desktop Specialist Exam Guide], a join is a way to combine table columns in relational databases by using shared values. A join can be inner, left, right, or full, depending on how the matching rows are included or excluded.

There are three benefits of using an extract as compared to a live connection to a data source:

A live connection to a data source can be slow due to network and user traffic, whereas a connection to an extract improves performance. An extract is a snapshot of data that is stored locally on your computer or on Tableau Server. An extract can reduce the load on the data source and speed up queries.

Extracts are stored in memory (RAM), resulting in faster query performance as compared with live data connections. When you use an extract, Tableau loads the data into memory and optimizes it for analysis. This allows Tableau to perform calculations and aggregations faster than with live connections.

Calculated fields perform better in workbooks connected to extracts than in workbooks with live connections to a data source. Calculated fields are custom fields that you create using formulas or expressions. When you use an extract, Tableau can process calculated fields more efficiently than with live connections.

In Tableau, a Density map (also known as a heat map) uses automatically generated sizes for the data points that cannot be resized by using the Marks card. This chart type is designed to display density of data points on a map, where the size and color of the data points represent the concentration of data in that area.

To invert the color intensity of a quantitative range in Tableau, you should use the "Reversed" option. This option inverts the color scheme so that the colors representing the higher values are swapped with those representing the lower values. For example, if a color scale initially shows dark colors for high values and light colors for low values, using "Reversed" will switch this so that dark colors represent low values and light colors represent high values. This option is particularly useful for better visual distinction and interpretation in certain data scenarios.

The following are the official definitions from the Tableau documentation for the various file types:

1) .tds (Tableau Data Source) - To not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you've made on top of the actual data such as changing default properties, creating calculated fields etc. (CORRECT ANSWER)

2) .twbx ( Tableau packaged workbook) - To create a single zip file that contains a workbook along with any supporting local file data and background images. This is great for sharing your work with others who don’t have access to the original data.

3) Extract (.hyper or .tde) – To create a local copy of a subset or entire data set that you can use to share data with others, when you need to work offline, and improve performance.

3) (.twb) Workbooks – To hold one or more worksheets, plus zero or more dashboards and stories.

Explanation

Data is generated and analyzed at many different levels of granularity. Granularity is the level of detail of the data. For example, when looking at graduation data, granularity would describe whether a row in the data set represents a single person or the graduating class of a university.

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

Yes, it is possible to disable highlighting for the entire workbook.

For more information : https://help.tableau.com/current/pro/desktop/en-gb/actions_highlight.htm

Explanation

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

In Tableau, a Fixed Level of Detail (LOD) expression calculates values at a specific level of granularity, regardless of the dimensions in the view. The computation of a fixed LOD expression can be influenced by a context filter. A context filter serves as a primary filter, setting the context for the rest of the filters in the view. When a context filter is applied, it effectively changes the level at which the fixed LOD expression is computed, thereby affecting its outcome. Other types of filters, such as table calculation, measure, and dimension filters, do not have this influence on fixed LOD expressions.

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!

An Individual Axis in Tableau is obtained by adding a continuous into Rows or Columns Shelf.

Example:

In order to show Individual Axis in Tableau First, we drag and drop the Color from Dimension shelf to Column Shelf. Next, we drag and drop the Sales Amount from measures shelf to Rows Shelf. Since it is a continuous value, the Sales Amount will be aggregated to default Sum. Once you drag them, following Chart report will be generated.

Next, we drag and Drop one more measure value, i.e., Total Product Cost from Measures Region to Rows Shelf. Because it is a Measure value, Total Product Cost is aggregated to default Sum. From the below screenshot, you can observe that Tableau has created an individual axis for each measure (continuous field).

Explanation

From the official Tableau website:

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).

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.

A Tableau story point is an individual container in a story that holds a sheet or dashboard. It's like a slide in a presentation, and a story is a sequence of these points that can be used to convey a data narrative, showing how facts are connected and guiding the audience through a sequence of analysis steps.

When users connect to Tableau, the data fields in their data set are automatically assigned a role and a type.

Role can be of the following two types:

1) Dimension

2) Measure

Type can be of the following :

1) String

2) Number

3) Geographic

4) Boolean

5) Date

6) Date and Time

Explanation

To interactively display information from the web INSIDE a dashboard, you can use a URL action with a web page object.

For example, you might have a dashboard that shows profits by country. In addition to showing the profit data in your dashboard, you also want to display supplemental information about the countries from a web site.

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.

To assign a color to marks in the view, do the following:

From the Data pane, drag a field to Color on the Marks card.

Tableau applies different colors to marks based on the field’s values and members. For example, if you drop a discrete field (a blue field), such as Category, on Color, the marks in the view are broken out by category, and each category is assigned a color.

If you drop a continuous field, such as SUM(sales), on Color, each mark in the view is colored based on its sales value.

According to the Tableau Help, one of the ways to improve a crosstab is to “Include an Other group”. The help also states that “If you have a large number of members in a dimension, you can create groups to combine low-frequency members into an Other group. This can help you focus on the most relevant data and reduce clutter in your view” (page 2).

When using a data source that has relationships, you can add a join between two or more tables by dragging a table directly on top of an existing logical table from the Tables pane. This will create a logical table that contains the joined tables. You can then edit the join type, join clauses, and join calculation as needed2 The other options are not valid ways to add a join between tables when using relationships. From the Tables pane, double-clicking a table will add it to the data source as a separate logical table, not joined with any other table. From the Connections pane, selecting Add will allow you to add another connection to the data source, not join tables within the same connection. Double-clicking a logical table in the canvas will open the Data Source page, where you can view and edit the fields in the logical table, not join it with another table2

Explanation

Remember that joins are defined in the physical layer and relationships in the logical layer.

You can still specify joins between tables in the physical layer of a data source. Double-click a logical table to go to the Join/Union canvas in the physical layer and add joins or unions.

Every top-level, logical table contains at least one physical table. Open a logical table to view, edit, or create joins between its physical tables. Right-click a logical table, and then click Open. Or, just double-click the table to open it.

When you create a data source, it has two layers. The top-level layer is the logical layer of the data source. You combine data between tables in the logical layer using relationships.

The next layer is the physical layer of the data source. You combine data between tables at the physical layer using joins. For more information, see Logical and physical tables in the data model

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).

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.

Hierarchies in Tableau allow users to drill up and down to explore data at different levels of detail. By setting up a hierarchy, users can navigate through levels of the hierarchy to analyze data at each level, from the highest summary down to the finest detail.

Explanation

Tableau auto-generates :

1 Dimension - Measure Names

4 Measures - Latitude, Longitude, Number of records, Measure Values

Starting with Tableau 2020.2, every table in a data source has a Count field, in the form of NameofTable(Count). The table count field is an automatically generated, calculated field. (THIS IS NOT PRESENT IN VERSION 2020.1 ON WHICH THE EXAM IS CURRENTLY BASED)