Desktop-Specialist Sample Questions Answers

Explanation

If you answered this question quickly and correctly, you're well prepared for the exam! Most students stumble while creating a Dual axis chart, so go ahead and give yourself a pat on the back!

To create a dual axis chart for the problem mentioned:

1) Drag Product Type to the column shelf, and Sales and Profit to the Row shelf:

2) Now, to focus on 2013, drag Date to the filter shelf and select only 2013:

3) Now, click on the Profit pill in the Rows Shelf, and select dual axis:

4) Now, in the marks shelf, choose Sales, and change the chart type to bar. Similarly, for Profit, change the chart type to Line.

Now the chart looks like this:

Now we change the Profit chart type to line:

5) Finally, we synchronise the axis as follows: Right click on the axis, and choose 'Synchronise axis'

And, our final view and answer is:

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.

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.

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.

You should use a relationship instead of a join for two data sets when the data sets include similar data aggregated at different levels of detail. A relationship is a way of combining data from different tables based on common fields without creating a single table with all fields. A relationship allows you to query data from multiple tables as needed and preserve the level of detail of each table. A relationship is useful when you have data sets that are aggregated at different levels of detail, such as sales by region and sales by product. A relationship can match data from different levels of detail without creating null values or duplicate rows. The other options are not valid situations for using a relationship instead of a join for two data sets. The data sets include similar data aggregated up to the highest level is not correct, because a relationship is not needed when both data sets have the same level of detail. You can use either a relationship or a join in this case, depending on your preference and performance. The data sets are in two separate tables within a single spreadsheet is not correct, because a relationship is not limited by the location or format of the data sets. You can use a relationship to combine data from different sources or connections, such as databases, files, or web services. To use both data sets across multiple sheets in a visualization is not correct, because a relationship does not affect how you use data in your visualization. You can use either a relationship or a join to create multiple sheets and dashboards with your data sets.

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:

Explanation

Line charts connect individual data points in a view. They provide a simple way to visualize a sequence of values and are useful when you want to see trends over time, or to forecast future values.

Please refer to the images 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:

You should save a workbook as a PDF document if you need paper copies of the workbook. A PDF document preserves the layout and formatting of the workbook, and can be easily printed or shared. Saving a workbook as a PDF document is not necessary or useful in the other situations1

When creating a group by selecting headers in a Tableau view, the newly created grouped dimension replaces the original dimension field on either the Rows or Columns shelf. This grouping action aggregates the selected headers into a single group, and this new group dimension is automatically placed in the view, replacing the original dimension. This functionality allows for more simplified and customized categorization within the data visualization, enhancing the ability to analyze and interpret data according to specific groupings.

Dates in Tableau will behave differently depending on whether they are a Datepart (blue) or a Datevalue (green). This affects how the axes display/behave and also how visualisations such as line charts will display. The difference essentially boils down to Dateparts behaving like a dimension as opposed to a measure which is how Datevalues behave. This means that Dateparts behave like discrete categories on the view whereas Datevalues are more like continuous numeric values.

Dateparts are discrete and they behave the same as dimension filters. If all dates are used on the filter then each individual date will be a datepart that can be selected/excluded. This is the same for each level of date, if datepart months is placed on filters January to December will be tick-able options in the filter. This also means that conditions and top/bottom filters can be applied to datepart filters like any other dimension filter.

Datevalues placed on filters behave like measure filters. A min and a max date can be set and there is a relative dates option which allows you to choose things like only show the previous 3 months or years etc.

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

Clearly, Regex Match is not one of these options!

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.

Read more in depth at : https://help.tableau.com/current/pro/desktop/en-us/actions_url.htm

Explanation

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

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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.

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When the Physical Tables option is selected for an extract in Tableau, an individual table is created for each physical table in the extract. This means that the extract will include a separate table for each underlying table in your database, maintaining the database's structure within the extract. This can be useful when you need to preserve the original granularity of the data or when working with certain database optimizations.

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.

From the official Tableau documentation:

You can union your data to combine two or more tables by appending values (ROWS) from one table to another. To union your data in Tableau data source, the tables must come from the same connection.

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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:

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

A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.

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

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

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

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

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".

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.

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 two types of aggregations that can be applied to string fields in Tableau are Count Distinct and Minimum. Count Distinct counts the unique values of a field, and Minimum finds the smallest value in a field based on the alphanumeric order. String fields do not support numeric aggregations like Sum or Average.

Explanation

Not too tough. Follow along the steps:

• Drag Color to Filter and choose Red:
• 3) Now to display the percentage correctly, lets format it. Click on the In Stock % pill in the Row shelf, and select format:
• And your final view will look like :

Explanation

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

You may create a context filter to:

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

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

Explanation

The word 'static tool' gives it away.

According to the official website :

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

Sets are custom fields that are created within Tableau Desktop based on dimensions from your data source. They are subsets of your data, which can be created manually or computed. Either dimensions or measures can be used to determine what is included or excluded from a set using conditional logic, but to CREATE a set we use dimensions.

Reference : https://interworks.com/blog/rcurtis/2016/10/26/tableau-deep-dive-sets-introduction-sets/

In Tableau, you can rename a field directly in the Data pane by clicking and holding on the field name until it becomes editable, allowing you to type a new name. Alternatively, you can use the drop-down menu associated with the field in the Data pane and select the "Rename" option. Both methods provide a quick and easy way to change the name of a field without affecting the underlying data structure. The "Format menu" and "Replace References" option do not apply to renaming fields.

We know that continuous fields will always create an axis, so options stating 'header' are automatically eliminated. For our question, see below:

Graphical user interface, text, application, email, Teams Description automatically generated

Had the question asked us to place this pill on the Rows shelf instead, we would've gotten a different answer:

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To provide additional information when hovering over a field in the Data pane, as shown in the exhibit, you need to configure a default comment for the field. This comment can be set by right-clicking on the field in the Data pane and selecting "Default Properties" and then "Comment." The text entered as a comment here will then be displayed as a tooltip when hovering over the field in the Data pane.

Explanation

Follow along to get the correct answer:

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

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

2.1 As it is (continuous)

2.2 Converting to discrete first & then using it

and then :

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

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

From the official documentation, the following are the major advantages of using Tableau Data Extracts:

From Tableau 2020.2 onwards, .hyper is the recommended way since it is faster than .tde!

Explanation

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

Explanation

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

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Explanation

One way to view a measure in Tableau Desktop is to split it into bins. You can think of bins as buckets based on a range of values. For example, say you have a measure that represents age. Instead of aggregating the measure to calculate the average age, you can bin the measure to define age groups: 0–5, 6–10, 11–15, and so on. Then you can count the number of people in each age group.

Create a calculated field for variable bin size

Step 1

Select Analysis > Create Calculated Field.

Step 2

In the Calculated Field dialog box, complete the following steps:

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.

 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

*Very important question*

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

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

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

Explanation

You can show trend lines in a visualization to highlight trends in your data.

To add trend lines to a view, both axes must contain a field that can be interpreted as a number. For example, you cannot add a trend line to a view that has the Product Category dimension, which contains strings, on the Columns shelf and the Profit measure on the Rows shelf.

However, you can add a trend line to a view of sales over time because both sales and time can be interpreted as numeric values.

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!

February is a discrete date part, because it is a specific value that can be used to group or filter data by month. 07Mar2017, 20Sep2016:9:8:8:6546, and 01/23/2021 are continuous date values, because they represent points along a continuous timeline that can be used for analysis.

Explanation

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

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

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

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

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

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

3) Click Save.

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

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Explanation

This is true, indeed!

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

Explanation

The data that you analyze in Tableau is often made up of a collection of tables that are related by specific fields (that is, columns). Joining is a method for combining data on based on those common fields. The result of combining data using a join is a virtual table that is typically extended horizontally by adding columns of data.

For example, consider the following two tables originating from a single data source:

We can combine these 2 tables, simply by joining the tables on ID to answer questions like, "How much was paid in royalties for authors from a given publisher?". By combining tables using a join, you can view and use related data from different tables in your analysis.

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 )

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

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

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.

Explanation

When you track data in Excel spreadsheets, you create them with the human interface in mind. To make your spreadsheets easy to read, you might include things like titles, stacked headers, notes, maybe empty rows and columns to add white space, and you probably have multiple tabs of data too.

When you want to analyze this data in Tableau, these aesthetically pleasing attributes make it very difficult for Tableau to interpret your data. That’s where Data Interpreter can help.

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.

All of the given options are true except - Animations work well with maps, polygons, and density marks in web browsers.

From the official documentation: 

As seen above, we can either turn the animations for the entire workbook (upper red box), or only for the current sheet ( lower red box )

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.

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 :)

Explanation

Follow along to reach the correct answer:

1) First, drag Date to the Column shelf and Profit to the Rows shelf. We need to see the 2 consecutive months over this two year period (2012-2013) so this tells us we need to work with continuous dates:

Click on Date in the Column shelf and convert it to continuous month :

2) Now, click on the Profit pill in the Rows shelf, go to quick table calculation and choose Percent difference:

3) Finally, click on the Show mark Labels icon:

4) We finally have our view, and clearly, 10 Months have a NEGATIVE percent difference:

Explanation

You can union your data to combine two or more tables by appending values (rows) from one table to another. To union your data in Tableau data source, the tables must come from the same connection.

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."

A union of these tables creates the following single table that contains all rows from all tables.

The Marks Card allows us not only to edit the Shape, Text and Colour, but also to modify the Tooltip and the level of detail of the visualisation!

The Marks card is a key element for visual analysis in Tableau. As you drag fields to different properties in the Marks card, you add context and detail to the marks in the view.

You use the Marks card to set the mark type (see Change the Type of Mark in the View), and to encode your data with color, size, shape, text, and detail. To change the mark settings, see Control the Appearance of Marks in the View.

In this example, three different fields have been dragged to different properties in the Marks card. Segment is on Color, Region is on Shape, and Quantity is on Size.

After you add a field to the Marks card, you can click the icon next to the field to change the property it is using. You can also click the property buttons in the Marks card to change those settings.

Many properties can have multiple fields. For example, you can add multiple fields to Label, Detail, Tooltip, and Color. Size and Shape can only have one field at a time. For more details, see Control the Appearance of Marks in the View.

All are correct, except - Copy of any local file-based data. This is contained in a .tdsx file (Tableau Packaged Data Source)!

According to the official documentation -

THIS IS A VERY IMPORTANT QUESTION

Aggregation is an important concept to consider when creating calculated fields. A calculated field for SUM([Profit]) / SUM([Sales]) will give you a very different answer than [Profit] / [Sales], even though both formulas are valid.

If you do not provide the aggregation within the calculated field, Tableau will calculate the equation for every record ( row ) in your analysis, then aggregate the answers for all of the rows together when the calculated field is added to the view.

In simple terms, if specify the aggregation such as SUM, what Tableau will do is that it will first calculate the sum of the Profit column ( say x ), then calculate the sum of the Sales column ( say y ), and then simply apply x/y ---> This is what we expect! Perfect!

BUT, if you don't specify the aggregation, it will go to every single ROW, perform Profit / Sales, and then aggregate the answers calculated for each row. This is simply NOT what we wan't!

An example:

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

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.

Scaled is NOT a valid size options when creating Dashboards in Tableau!

After you create a dashboard, you might need to resize and reorganize it to work better for your users.

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.

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:

Important question! You cannot use a context filter to replace a data source filter since each filter type has its own use case. Also, a content filter is an Independent filter and all other filters are called dependent since they only process the data that passes through a context filter.

According to the official documentation : 

Explanation

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

Follow the steps below:

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.

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

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.

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

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:

A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.

The basic building blocks for a histogram are as follows:

Demo :

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

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

Important question!

To combine data from another database with an existing data source in Tableau, the first step is to add a new connection. This will allow you to access the additional database and either blend or join the data from the two sources depending on your analysis needs.

Explanation

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

Of course! Follow along:

Right click on any measure, and choose Discrete as shown:

Once you do this, the green pill becomes blue in colour, indicating that it is now Discrete!

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)

You should select Size on the Marks card and use the slider to adjust the size to uniformly change the size for all marks in a view. The Size property on the Marks card allows you to control the size of marks in the view by moving the slider to the left or right. The Size slider affects different marks in different ways, such as making them bigger or smaller, wider or narrower, or thicker or thinner1 The other options are not valid ways to uniformly change the size for all marks in a view. Selecting Label on the Marks card and then selecting Alignment will allow you to change the position of labels on marks, not the size of marks2 Using the Fit dropdown menu on the toolbar will allow you to change how the view fits within the worksheet, not the size of marks3 Selecting Format on the menu, and then selecting Cell Size will allow you to change the height and width of cells in a text table, not the size of marks in other types of views4

Explanation

According to Tableau's official documentation -

Explanation

As the question mentions, we need to create a SET with the following conditions -> Choose only those customers whose Sales > 30,000

1) Right click on customer name --> Create --> Set

2) Let's Name the Set - Customer>30k ( you can name it anything you want :) )

Select USE ALL, and then move to the CONDITION TAB:

3) In the Condition Tab, Choose BY FIELD -> Select Sales -> Sum -> Greater than 30000 , and click OK

4) You should now have a new Set in the Data Pane as follows:

5) Drag this set to the rows shelf, and click on SHOW MEMBERS IN SET. Now drag Sales to the Column Shelf.

6) Click on the Show Mark Labels, and Sort ascending icons as shown:

7) Voila! We have our answer:

c

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.

Explanation

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

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

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

Explanation

To reach the correct answer, follow the steps below:

1) Drag Category, and sub-category to the row shelf. Drag Profit to the Column shelf

2) Click the Sort-ascending icon as shown above, to sort the profits from least to greatest as shown:

Click the 'Show mark labels icon'

As we can see, Fasteners has the least Profit in the Office Supplies Category, and hence is our correct answer!

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

Distribution Pane

Explanation

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

Explanation

Follow along the steps below:

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