TDS-C01 Tableau Desktop Specialist Question and Answers

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.

Explanation

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

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

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.

Therefore, we need at least 2 measures for creating bullet graphs.

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!

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

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.

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).

Lot of students have been seeing this question in the exam lately, and wanted me to include this question so here it is. Follow along -

1) Click on Worksheet in the Menu bar, followed by Tooltip and select the bold option

2) Click on Tooltip in the Marks card, and select bold.

Graphical user interface, application Description automatically generated

3) Right click, click format and then under the default worksheet formatting, choose Tooltip and make it bold.

A picture containing line chart Description automatically generatedGraphical user interface Description automatically generated

There exists no option to Bold the tooltip contents by clicking Analysis. Hence, it is an incorrect choice.

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.

Video is NOT a valid object type while creating dashboards in Tableau! All others are valid object types.

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.

No, by default, animations are not enabled in Tableau.

We can animate visualizations to better highlight changing patterns in your data, reveal spikes and outliers, and see how data points cluster and separate.

Animations visually transition between filter, sort, and zoom settings, different pages, and changes to filter, parameter, and set actions. As visualizations animate in response to these changes, viewers can more clearly see how data differs, helping them make better informed decisions.

When you author animations, you can choose between two different styles: simultaneous or sequential. Here are examples of each type.

1) Simultaneous animations

The default simultaneous animations are faster and work well when showing value changes in simpler charts and dashboards.

2) Sequential animations

Sequential animations take more time but make complex changes clearer by presenting them step-by-step.

To Animate visualizations in a workbook:

1) Choose Format > Animations.

2) If you want to animate every sheet, under Workbook Default, click On. Then do the following:

For Duration, choose a preset, or specify a custom duration of up to 10 seconds.

For Style, choose Simultaneous to play all animations at once or Sequential to fade out marks, move and sort them, and then fade them in.

3) To override workbook defaults for a particular sheet, change the settings under Selected Sheet.

To display your company's web page on a Tableau dashboard, you should use a web page object. The web page object allows you to embed a web page within your Tableau dashboard, providing direct access to external web content.

Open your Dashboard: Start by opening the dashboard where you want to add the web page.

Add Web Page Object: In the Objects section of the dashboard pane, select the "Web Page" object and drag it onto your dashboard.

Configure URL: After placing the web page object, a dialog box will prompt you to enter the URL of the web page you want to display. Enter your company's web page URL here.

Resize and Position: Adjust the size and position of the web page object to fit your dashboard design.

References:

Tableau's official documentation on dashboard objects: Dashboard Objects

When exporting a view as an image in Tableau, the default export includes everything that is currently displayed in the view, with Tableau applying its own styling, including fonts. The default format for an exported image is PNG, which is a raster-based file format that captures all visual elements as pixels. PNG is widely used for its lossless compression and is suitable for detailed images like those produced by Tableau. Unlike vector-based images, PNGs do not embed fonts, and the image quality remains consistent when the image is viewed on different platforms, which makes it ideal for inserting into documents like Microsoft Word.

Explanation

Measures contain numeric quantitative values hence that option is incorrect.

Reference 1: https://help.tableau.com/current/pro/desktop/en-us/datafields_typesandroles.htm

Reference 2: https://help.tableau.com/current/pro/desktop/en-us/dates.htm

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.

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."

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.

According to the Tableau Desktop Specialist Exam Guide, city, country, and airport are three geographic roles that you can assign to a field. Address and time zone are not geographic roles in Tableau.

In fact, the opposite of this is true.

Trick : Whenever you think of joins -> Think that after the join is created, we get 1 single flat combined (joined) table. This flat combined table is created prior to us creating our visualizations. This happens at the physical layer.

If you ever think about relationships, know that all tables will remain distinct and separate, and relationships sit at the logical layer. At run time, when you bring in the dimensions and measures to create your viz, Tableau very smartly creates the necessary joins, relates the tables and sends queries to these tables to get the resultant data back in the most meaningful way possible. This allows you to focus on using your data and revealing insights from it and focus less on the data preparation aspect!

Refer to logical layer vs physical layer from the official documentation: https://help.tableau.com/current/server/en-us/datasource_datamodel.htm

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).

Two use cases for creating hierarchies from the Data pane are to add drilldown functionality for fields and to organize related fields together. A hierarchy is a way of organizing data into different levels of detail. For example, a date hierarchy can have year, quarter, month, and day levels. A geographic hierarchy can have country, state, city, and zip code levels. By creating hierarchies from the Data pane, you can quickly drill down or up in a hierarchy to add or subtract more levels of detail in the view. You can also use hierarchies to group related fields together in the Data pane, making it easier to find and use them14 The other options are not valid use cases for creating hierarchies from the Data pane. To concatenate all fields into a single field, you need to use a calculated field or a join, not a hierarchy. To create faster-performing queries, you need to optimize your data source, filters, calculations, or extracts, not create hierarchies

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.

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

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 )

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.

Very important question for the exam and appears quite a lot too.

The correct answer is - By dragging another dimension to Color on the Marks card.

This is what the question says we have already created. Now to convert this into a Stacked bar chart, we will drop another dimension on Color in the Marks card.

The rest won't create stacked bar charts, and hence are incorrect choices. The best way to answer such questions on the real exam is to quickly do what the options say and see if they satisfy the requirements in the question.

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.

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

Since you need BOTH State and the YEAR, we need to use an Inner Join.

Follow the steps below:

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 icon shown is used to add a new Dashboard! From the official documentation:

From the official documentation:

When you have a view with a large amount of data you might want to explore your data interactively and highlight a specific mark or group of marks while still maintaining the context of where those marks show in your view.

To do this you can turn on the Highlighter for one or more discrete fields that are included in your view and that affect the level of detail

Example - Here we just want to focus on Public Affairs college dimension, but don't want to filter out or remove the rest of the data:

Note that filtering is not the correct option since that would REMOVE the data that doesn't match the filtering criteria.

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

The benefits of using a live connection over an extract include:

B: A live connection ensures that the data in the workbook is as up-to-date as the database itself, providing fresher data compared to a static extract which is updated at intervals.

C: A live connection queries the database server directly, which means it uses the server's memory and processing power rather than relying on the client computer's resources.

A live connection does not necessarily require less network overhead (A) as it may continually send queries over the network, and it is not always faster than an extract (D) because extracts can provide quicker response times for complex queries or large datasets.

 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

Explanation

You can create aliases (alternate names) for members in a dimension so that their labels appear differently in the view.

Aliases can be created for the members of discrete dimensions only. They cannot be created for continuous dimensions, dates, or measures.

To create an alias:

1) In the Data pane, right-click a dimension and select Aliases.

2) In the Edit Aliases dialog box, under Value (Alias), select a member and enter a new name.

To submit your changes: In Tableau Desktop, click OK.

On Tableau Server or Tableau Online, click the X icon in the top-right corner of the dialog box.

When you add the field to the view, the alias names appear as labels in the view. For example:

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 displays data source connections and data fields for the workbook in the Data pane on the left side of the workspace.

The Data pane includes:

Dimension fields – 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. Examples of dimensions include dates, customer names, and customer segments.

Measure fields – Fields that contain numeric, quantitative values can be measured. You can apply calculations to them and aggregate them. When you drag a measure into the view, Tableau applies an aggregation to that measure (by default). Examples of measures: sales, profit, number of employees, temperature, frequency.

For more information on what dimensions and measures are, see Dimensions and Measures, Blue and Green.

Calculated fields – If your underlying data doesn't include all of the fields you need to answer your questions, you can create new fields in Tableau using calculations and then save them as part of your data source. These fields are called calculated fields.

For more information on calculated fields, see Create Custom Fields with Calculations.

Sets – Subsets of data that you define. Sets are custom fields based on existing dimensions and criteria that you specify. For more information, see Create Sets.

Named sets from an MS Analysis Services server or from a Teradata OLAP connector also appear in Tableau in this area of the Data pane. You can interact with these named sets in the same way you interact with other custom sets in Tableau.

Parameters – Values that can be used as placeholders in formulas, or replace constant values in calculated fields and filters. For more information, see Create Parameters.

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:

It is clear that October with -55.3% had the lowest Year on Year growth.

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.

Further,

Hierarchies in Tableau are used to define a drill-down path through your data. By creating a hierarchy, you can organize related fields together, which makes it easier to navigate complex data models. This also allows users to explore data at different levels of detail, from the highest level of the hierarchy to the most granular details, simply by clicking to expand and collapse levels of the hierarchy in the view.

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.

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 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.

You can perform two actions when you join tables from multiple connections: add a data source filter and create an extract. A data source filter is a filter that you can apply to the data source before it is loaded into Tableau. This can help improve performance and reduce the amount of data in the view. A data source filter can be applied to any data source, including those that use cross-database joins2 An extract is a snapshot of data that is stored locally on your computer or on Tableau Server. An extract can also improve performance and enable offline analysis. You can create an extract from any data source, including those that use cross-database joins3 You cannot perform the other two actions when you join tables from multiple connections: create a union or use a stored procedure. A union is a method for combining data by appending rows of one table onto another table. To union your data in Tableau, the tables must come from the same connection. You cannot union tables from different data sources or connections4 A stored procedure is a set of SQL statements that can be executed on a database server. Tableau does not support using stored procedures as part of a cross-database join. You can only use stored procedures with some single-connection relational data sources, such as Microsoft SQL Server, Oracle, or PostgreSQL5

You can assign an alias to a field member before creating a visualization. An alias is an alternative name that you can assign to a value in a dimension field. You can use aliases to rename specific values within a dimension to make them more relevant or descriptive in your view than what the original data provides. For example, you can use aliases to shorten long names, correct spelling errors, or replace codes with meaningful labels6 You can create aliases for the members of discrete dimensions only. They cannot be created for continuous dimensions, dates, or measures. To create an alias for a dimension member, you can right-click the dimension in the Data pane and select Aliases, then enter a new name for each member under Value (Alias). You can also create an alias by right-clicking a dimension member in the view and selecting Edit Alias. You can do this before or after creating a visualization6 The other options are not accurate statements about aliases. You cannot create an alias for a discrete measure, because measures are not discrete fields. You cannot create an alias for a continuous dimension, because aliases are only available for discrete dimensions. When you assign an alias, the name does not change in the database, only in Tableau. Aliases are stored as part of the workbook or data source, and do not affect the original data6

Layout containers let you group related dashboard items together so you can quickly position them. As you change the size and placement of items inside a container, other container items automatically adjust

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.

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!

Explanation

Yes, it is possible to create worksheet-specific filters in Tableau.

When you add a filter to a worksheet, by default it applies to the current worksheet. Sometimes, however, you might want to apply the filter to other worksheets in the workbook.

Then, you can select specific worksheets to apply the filter to or apply it globally to all worksheets that use the same data source or related data sources.

In Tableau, you can change the font of a worksheet title by double-clicking directly on the title in the view, which opens a dialog box where you can format the text, including changing the font. Another method is to use the Format menu; from there, you select "Title and Caption," which opens the Format Title pane on the left side of the screen, where you can change the font and other formatting options for the worksheet title.

In Tableau, you can aggregate measures or dimensions, though it is more common to aggregate measures. Whenever you add a measure to your view, an aggregation is applied to that measure by default. The type of aggregation applied varies depending on the context of the view.

When you add a measure to the view, Tableau automatically aggregates its values. Sum, average, and median are common aggregations; for a complete list, see List of Predefined Aggregations in Tableau.

The current aggregation appears as part of the measure's name in the view. For example, Sales becomes SUM(Sales). Every measure has a default aggregation which is set by Tableau when you connect to a data source. You can view or change the default aggregation for a measure—see Set the Default Aggregation for a Measure.

You can change the aggregation for a measure in the view from its context menu:

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

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 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

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

Remember that dragging a discrete value to colour creates distinct colours for each item whereas dragging a continuous value to colour creates a gradient. ( Same for Map )

From the official documentation:

Padding lets you precisely space items on dashboard, while borders and background colors let you visually highlight them. Inner padding sets the spacing between item contents and the perimeter of the border and background color; outer padding provides additional spacing beyond the border and background color.

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.

Tableau will automatically create a hierarchy for date and geographic data. A hierarchy is a way of organizing data into different levels of detail. For example, a date hierarchy can have year, quarter, month, and day levels. A geographic hierarchy can have country, state, city, and zip code levels. Tableau recognizes date and geographic data based on their data types and formats, and creates hierarchies for them by default. Tableau does not automatically create hierarchies for date & time or string data3

You can combine two sets to compare the members. When you combine sets you create a new set containing either the combination of all members, just the members that exist in both, or members that exist in one set but not the other.

Combining sets allows you to answer complex questions and compare cohorts of your data. For example, to determine the percentage of customers who purchased both last year and this year, you can combine two sets containing the customers from each year and return only the customers that exist in both sets.

To combine two sets, they must be based on the same dimensions. That is, you can combine a set containing the top customers with another set containing the customers that purchased last year. However, you cannot combine the top customers set with a top products set.

Explanation

The word 'static tool' gives it away.

According to the official website :

Presently, there is no official way to connect your data in Firebase directly with Tableau Desktop.

A workaround however can be to export your Firebase data into Google BigQuery, and then connect it to Tableau Desktop.

But then again, it is a workaround and not an official out-of-the-box solution.

The following are the available Data sources available as of now:

1) Server

2) File

Explanation

Phew! Tricky one! You needed to use filters in this one.

Follow along:

2) Next, as the question mentions, we need to focus on the Assortment PHONE, the color WHITE, and the state of NEW YORK. -> so we use filters for this!

i) First drag Assortment to Filters, and select only Phones :

ii) Next, drag Color to Filters and Choose only White:

iii) Next, drag State ID to Filters, and choose New York (NY):

And Voila! We have our answer as follows:

iv) Last, drag Sales to Label:

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!

The following showcase how you can show mark labels. Using the Sample Superstore dataset:

1) Let's create a Bar chart showing the sales for each sub-category:

2) Now you can show labels by:

2.1) Click on Show Mark Labels Icon in the Toolbar ( easiest )

2.2) Drag Sales to the Text icon in the Marks Card:

2.3) Click on Analysis -> Show mark labels from the Tableau menu bar:

Explanation

To reach the correct answer, follow these steps:

1) Drag Order Date (Discrete Year) to the Column shelf, and Region to the Row Shelf as shown:

2) Drag Profit to Text in the Marks Shelf as shown:

3) Click on Analysis as shown -> Totals -> SELECT ROW GRAND TOTALS

The following will be the final view:

You could also Filter by Region to only Focus on Canada, but that's your choice:

THEREFORE,

2012 = 4,888

2011 -> 2014 = 17,817

Tableau Desktop will display marks by using a diverging palette as the default to display data that has both negative and positive quantitative values. A diverging palette is a type of color palette that uses two different color ranges to show positive and negative values. For example, a red-green diverging palette uses shades of red for negative values and shades of green for positive values. A diverging palette is automatically applied when there are both negative and positive values for a measure that is placed on Color on the Marks card5 The other options are not correct types of color palettes that Tableau Desktop uses as the default for data with both negative and positive values. A full color range is not a valid term for a color palette in Tableau. A sequential palette is a type of color palette that uses different shades of one color to show variations in a single measure. A sequential palette is usually applied when there are only positive values for a measure that is placed on Color on the Marks card5 A categorical palette is a type of color palette that uses different colors to show discrete values or categories. A categorical palette is usually applied when there is a dimension that is placed on Color on the Marks card5

 A dual axis chart is useful for comparing two measures that have different scales. A dual axis chart is a type of visualization that shows two measures using two independent axes layered on top of one another. A dual axis chart allows you to compare and contrast two measures that have different ranges or units of measurement, such as sales and profit margin, temperature and precipitation, or population and GDP per capita. A dual axis chart can also show different mark types for each measure, such as bars and lines, circles and areas, or shapes and texts. The other options are not valid reasons for using a dual axis chart for comparing two measures. Have little in common is not correct, because a dual axis chart is meant to show some kind of relationship or correlation between two measures, not just contrast them. Are Table Calculations is not correct, because a dual axis chart can be used with any type of measure, whether it is an aggregation, a calculation, or an expression. Are aggregated Dimensions is not correct, because a dual axis chart cannot be used with dimensions, only with measures. Dimensions are fields that contain qualitative values that are used to categorize or segment data, not compare them.

**IMPORTANT QUESTION AND EXPLANATION, PLEASE READ**

3 ways to group data -

1) Marks

2) Labels

3) Dimensions shelf.

*IMPORTANT*

If we Group the data by selecting the marks, then they remain separate marks in the view and then have the same colour. Also, a new group is created in the Dimensions shelf. Example -

Using the sample superstore dataset, first plot a bar chart showing sales for each sub-category:

Here, if we Select Phones, Chairs and Storage by selecting the MARKS (Bars), and then group them:

They remain seperate marks (BARS) but are grouped by the same colour.

Now, if we didn't do this, and rather grouped by selecting their Labels (Names):

Then they no longer remain separate Marks (bars) but are rather consolidated into a single Bar:

Finally, we can group directly from the Dimensions shelf as follows:

Now choose Phones, Chairs and Storage and Click Group:

You will now automatically have a new Dimension as follows:

Measure Names is a dimension. Latitude, Longitude, and Number of records are all measures.

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.

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

Explanation

Since we need to focus on 1 country -> Japan, let's filter on it first as follows:

1) Drag Country to the filter shelf, and choose only Japan. Click OK.

2) Read the Question Carefully, we need to break down the visualisation by Region, then by Country, and then by State. So let's do that:

Drag Region to the column shelf, followed by Country. Drill down into Country to include states as well.

Then drag Quantity to the Row Shelf, and change the Aggregation to AVERAGE.

The following is our visualisation:

Now that you think of it, EVEN IF YOU REMOVE THE REGION, THE ANSWER REMAINS THE SAME. Such elements will be present in the actual exam too, just to make the question sound a little difficult, but actually it is pretty straightforward :)

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

Beginning in version 10.5, when you create a new extract, it uses the .hyper format instead of the .tde format.

Extracts in the .hyper format take advantage of the improved data engine, which supports the same fast analytical and query performance as the data engine before it, but for even larger extracts.

Although there are many benefits of using .hyper extracts, the primary benefits include the following:

1) Create larger extracts: You can create extracts with billions of rows of data. Because .hyper extracts can support more data, you can consolidate .tde extracts that you previously had to create separately into a single .hyper extract.

2) Create and refresh extracts faster: While Tableau has always optimized performance for creating and refreshing extracts, version 2020.3 supports faster extract creation and refreshes for even larger data sets.

3) Experience better performance when interacting with views that use extract data sources: Although smaller extracts continue to perform efficiently, larger extracts perform more efficiently.

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.

Explanation

You can add a reference line to any continuous axis in the view.

To add a reference line:

Drag Reference Line from the Analytics pane into the view. Tableau shows the possible destinations. The range of choices varies depending on the type of item and the current view.

In a simple case, the drop target area offers three options:

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.

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

View Data allows you to inspect your data in a spreadsheet-like layout. You can view data either for the data source as a whole, or to see the underlying data for an individual mark or a group of marks. In a worksheet, the rows that you see in the View Data window are always scoped to the current selection or the current view.

The View Data window displays as much of the data as possible by default, up to 10,000 rows. Field names are shown as column headers and can be dragged and dropped to change their display order. Click a column header to sort the values in that column.

From the official website:

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.

To display multiple distinct lines on the same axis based on a field, you should place the field on the Color shelf in the Marks card. This will encode each distinct value in the Region field with a different color, resulting in separate lines for each region on the same axis.

From the data pane, simply right click on the dimension, choose geographic role, and then select the appropriate role as follows:

To perform a union in Tableau, the tables must have a related field with matching data types, and they must have the same number of fields. This allows the tables to be appended vertically in the data source. Different names or tables from different connections do not affect the ability to union the tables.

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

Bar charts in Tableau do not require a dimension to be created. You can create a bar chart using only a measure; this will produce a single bar that represents the aggregate of the measure values, such as the sum or average of sales.

The LATEST Tableau Desktop Sepcialist exam blueprint now requires you to know some basics about animations as well!

NOTE: Animations are DISABLED by default and must be manually enabled.

You can also reset all settings to default by clickin on 'Reset All'

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.

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!

Explanation

It is possible in Tableau to use a sheet within a story directly.

Moreover, in Tableau, a story is a sequence of visualizations that work together to convey information. You can create stories to tell a data narrative, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case.

At the same time, a story is also a collection of sheets, arranged in a sequence. Each individual sheet in a story is called a story point.

Explanation

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