Desktop-Specialist Tableau Desktop Specialist Exam Questions and Answers

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

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:

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

Clearly, Regex Match is not one of these options!

According to the Tableau Help, headers are “labels that identify the different parts of your view”. The help also states that “Headers are created when you place a discrete dimension on Columns or Rows” (page 1).

Explanation

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

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

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

Explanation

Follow the steps to get the correct answer : January 2018

• We are talking about dates, so use the Time series sheet as follows:
• Next, the following should be your view and clearly, January 2018 is the lowest point:

Read more about dates: https://interworks.com/blog/rcurtis/2017/01/30/tableau-deep-dive-dates-introduction-dates/

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.

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

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.

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

Explanation

VERY IMPORTANT QUESTION FOR THE EXAM, PAY ATTENTION

1) To find the number of days between order date and shipping date, we will make use of a calculated field:

In the data pane, click on the dropdown arrow, and choose create calculated field.

Let's name this calculated field "ShippingDelay" (you can name it anything you want :) )

2) Use the DATEDIFF() function, and pass it the arguments as follows:

'day' depicts that we want to calculate the number of DAYS between the two dates. The first argument is 'start_date' which is the ORDER_DATE (day the order was placed), the second argument is 'end_date', which is the SHIP_DATE (date the order was shipped). So by subtracting as follows: SHIP_DATE - ORDER_DATE, we can find the delay in shipping.

Click OK.

3) You should now have a new measure as follows:

4) Phew! The hard part is done! Now let's filter by Market to include only LATAM:

5) Drag Country to the view, and the new calculated field 'ShippingDelay' to SIZE on the Marks Shelf as follows:

*You can also click on Show Text Labels to be sure that you're choosing the Largest value*

Clearly, Mexico has the highest Shipping Delay!

Explanation

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

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

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

Explanation

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

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

To assign a geographic role to a field:

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

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

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

Explanation

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

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

Explanation

According to the official Tableau documentation, there are 5 types of trend lines which we can work with in Tableau :

1) Linear Trend Line

2) Logarithmic Trend Line

3) Exponential Trend Line

4) Polynomial Trend Line

5) Power Model

Hence, the correct answer is BINOMIAL trend line which is not present in Tableau.

See the following image:

For more information, refer to: https://help.tableau.com/current/pro/desktop/en-us/trendlines_add.htm

With dimension filters in Tableau, you can use several filter modes, including "Multiple Values (drop-down)" which allows users to select one or more values from a drop-down list of all the dimension's members. Another mode is "Wildcard Match," which lets users filter the view by typing in a text box to match dimension members that contain the typed string. These filter types are particularly useful for string or categorical dimensions where users need to search or select specific members to display in the view.

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

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

We can use scatter plots to visualize relationships between numerical variables!

In Tableau, you create a scatter plot by placing at least one measure on the Columns shelf and at least one measure on the Rows shelf (Total 2 minimum). If these shelves contain both dimensions and measures, Tableau places the measures as the innermost fields, which means that measures are always to the right of any dimensions that you have also placed on these shelves. The word "innermost" in this case refers to the table structure.

 ( Simple Scatter Plot)

 (Matrix of Scatter Plots)

A scatter plot can use several mark types. By default, Tableau uses the shape mark type. Depending on your data, you might want to use another mark type, such as a circle or a square. For more information, see Change the Type of Mark in the View.

To create a scatter plot, follow the steps below:

 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.

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

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!

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.

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:

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 :

Distribution Pane

Explanation

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

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.

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

Explanation

After making changes to Data, we can save that new data source as a .tds file. To do so, go to data menu on top and then choose your current connected data source. Then next click on Add to Saved Data sources. This will save all calculated fields, changes to fields etc. It will be saved in My Tableau Repository -> Mydatasources. This will then also appear on Tableau Home Page under saved data sources like SampleSuperStore.

Note: Data source files do not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you've made on top of the actual data such as changing default properties, creating calculated fields, adding groups, and so on.

twb and .twbx are not the BEST solutions since the questions nowhere mentions that we need to store our workbooks as well.

twm is a bookmark which contains a single worksheet and are an easy way to quickly share your work.

Explanation

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

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

This is a tricky question often asked in the exam.

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

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

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

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

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

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

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

Explanation

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

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

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

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

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

According to the official Tableau documentation:

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

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

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!

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!

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

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

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:

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

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!

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

When creating an extract in Tableau, there are several options to control how much data is included in the extract. These options include hiding all unused fields to reduce the size of the extract, aggregating the data for visible dimensions to summarize it, and applying filters to extract only the data that meets certain criteria.

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

Replace References: 

When you successfully connect to a new data source, all worksheets in the workbook that previously referred to the original data source now refer to the new data source. If the new data source does not have the same field names as the original workbook, the fields become invalid and are marked with an exclamation point . You can quickly resolve the problem by replacing the field’s references.

For example, say you have a workbook connected to a data source that contains a Customer Name field. Then you edit the data source to point to a new data source that has all the same data but instead of Customer Name, the field name has been changed to Name. The Customer Name field remains in the Data pane but is marked as invalid. To make the field valid, you can replace the references, which means you can map the invalid field to a valid field in the new data source (for example, Customer Name corresponds to Name).

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

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:

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.

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.

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.

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

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

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

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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:

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.

Explanation

The following are 2 correct ways to copy the worksheet visualisation as an image:

AND

Explanation

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

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.

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.

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

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

Example:

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

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

Explanation

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.

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

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.

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

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

You can change the scope of a reference line by choosing one of the following options: Per Pane, Entire Table, or Per Cell. The scope determines how many reference lines are added to the view and how they are calculated. Per Pane adds one reference line for each pane in the view. Entire Table adds one reference line for the entire table in the view. Per Cell adds one reference line for each cell in the view

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

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:

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

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

THIS IS A VERY IMPORTANT QUESTION

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

Explanation

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!

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.

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

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

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!

**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:

Extracts would be more beneficial for analyzing historical prices where we won't be making use of any real time data being streamed. Same is the case for enormous datasets having billions of rows (extracts will be more efficient in analyzing subsets of such large data).

As for live stock prices, flight updates, real time updates from production or mission critical systems - having a live connection is the most logical choice, since we need access to the most fresh and recent data possible at all times!

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.

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.

According to the official Tableau documentation:

An example of an area chart is shown below:

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.

According to the Tableau Desktop Specialist Exam Readiness, a line chart will be created whenever you place measures on one shelf, and a date dimension on the other. This is because Tableau automatically recognizes date fields and treats them as continuous dimensions.

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

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

Explanation

Tableau auto-generates :

1 Dimension - Measure Names

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

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

From the official Tableau documentation:

As we can see below, Bar charts can be used as a floating object.

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.

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

TWBX is all in one. It contains viz, info needed to build the viz, and a copy of the data source. It doesn’t contain extracts of the data but can contain both live and data extracts. Best if want to eliminate the barrier of data access.

Create a .twbx with file-based data sources

1) Select File > Save As.

2) Specify a file name for the packaged workbook in the Save As dialog box.

3)Select Tableau Packaged Workbooks on the Save as type drop-down list.

4) Click Save.

5) The default location is the Workbooks folder of the Tableau repository. However, you can save packaged workbooks to any directory you choose.

The following files are included in packaged workbooks:

--> Background images

--> Custom geocoding

--> Custom shapes

--> Local cube files

--> Microsoft Access files

--> Microsoft Excel files

--> Tableau extract files (.hyper or .tde)

--> Text files (.csv, .txt, etc.)

Explanation

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

Step 1: Drag a date field to the filter shelf

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

Step 2: Select a time unit

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

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

To clear all sorting in a Tableau visualization, you would go to the Worksheet menu, select the "Clear" option, and then choose "Sorts." This action removes all sorting that has been applied to the visualization, including any custom sorting or sorting based on multiple fields. This is a quick way to reset the view to its default sorting state and is particularly useful when you have applied various sorting layers and wish to start fresh.