Tableau Desktop-Specialist Tableau Desktop Specialist Exam Exam Practice Test

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).

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!

When you click Salt Lake City in the view, the URL action will direct you to A URL action is a hyperlink that points to a web page 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 URLs3 In this case, the URL action uses as the URL target, where is a field value from the view. When you click Salt Lake City in the view, Tableau will replace with Salt Lake City in the URL target. However, since spaces are not allowed in URLs, Tableau will encode them as + signs instead. Therefore, the final URL will be 3 The other options are not correct because they do not reflect how Tableau encodes field values in URL actions.

 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.

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.

*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:

If you’ve created a data connection that you might want to use with other workbooks or share with colleagues, you can export (save) the data source to a file. You might want to do this also if you’ve added joined tables, default properties, or custom fields—such as groups, sets, calculated fields, and binned fields—to the Data pane.

Visualisations and Data extracts are NOT saved in a .tds file!

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.

A story is a sheet, so the methods you use to create, name, and manage worksheets and dashboards also apply to stories (for more details, see Workbooks and Sheets). At the same time, a story is also a collection of sheets, arranged in a sequence. Each individual sheet (worksheet or dashboard) in a story is called a story point.

When you share a story —for example, by publishing a workbook to Tableau Public, Tableau Server, or Tableau Online—users can interact with the story to reveal new findings or ask new questions of the data.

According to Tableau's official documentation:

A picture containing application Description automatically generated

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.

Explanation

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

1) Select

2) Hover

3) Menu

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

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.

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

Explanation

According to Tableau's official documentation -

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.

Explanation

Data fields are made from the columns in your data source. Each field is automatically assigned a data type (such as integer, string, date), and a role: Discrete Dimension or Continuous Measure (more common), or Continuous Dimension or Discrete Measure (less common).

Dimensions 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.

Measures contain numeric, quantitative values that you can measure. Measures can be aggregated. When you drag a measure into the view, Tableau applies an aggregation to that measure (by default).

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.

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:

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

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 : 

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 :

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

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

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:

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.

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'

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:

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

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

The computer on which you are installing or upgrading Tableau Server must meet the minimum hardware requirements. If the Setup program determines that your computer does not meet the following requirements, you will not be able to install Tableau Server.

These minimum requirements are appropriate for a computer that you use for prototyping and testing of Tableau Server. They apply to single-node installations and to each computer in a distributed installation.

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.

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

• A live connection to a data source can be slow due to network and user traffic, whereas a connection to an extract improves performance. An extract is a snapshot of data that is stored locally on your computer or on Tableau Server. An extract can reduce the load on the data source and speed up queries.
• Extracts are stored in memory (RAM), resulting in faster query performance as compared with live data connections. When you use an extract, Tableau loads the data into memory and optimizes it for analysis. This allows Tableau to perform calculations and aggregations faster than with live connections.
• Calculated fields perform better in workbooks connected to extracts than in workbooks with live connections to a data source. Calculated fields are custom fields that you create using formulas or expressions. When you use an extract, Tableau can process calculated fields more efficiently than with live connections.

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

Explanation

Chart Description automatically generated

Explanation

Cluster analysis partitions marks in the view into clusters, where the marks within each cluster are more similar to one another than they are to marks in other clusters.

Explanation

Trend lines have become popular questions in recent Tableau examinations. Follow along:

1) First drag Sales to the Rows shelf and Profit to the Columns shelf:

c

You will only see a single mark since the view is aggregated.

2) Now, break down this view by state. Drag State into Detail on the Marks shelf ( or directly to the view):

3) Finally, move to the Analytics pane, and drag Trend line to the view. When you drag it, select the Linear option!:

4) The following is our view. Hover over the trend line to see the R-squared value:

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!

The following options are available in the Device preview section when creating a Dashboard:

Graphical user interface Description automatically generated

Explanation

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

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.

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

Explanation

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

Follow the steps below:

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.

Two correct methods for creating a visual group are selecting marks in the view and right-clicking a dimension in the Data pane. A visual group is a way of combining related members in a dimension field to create categories or segments in your data. For example, you can create a visual group by selecting several states in a map view and grouping them into regions. You can create a visual group by selecting one or more marks in the view and then clicking the group icon on the tooltip or on the toolbar. This will create a new group field in the Data pane with default names for each group based on their members. You can also create a visual group by right-clicking a dimension in the Data pane and selecting Create > Group. This will open the Create Group dialog box where you can select several members and drag them into groups with custom names8 The other options are not correct methods for creating a visual group. Clicking the drop-down arrow from the top of the Data pane will open a menu with options for creating new fields, folders, sets, bins, etc., but not groups. Dragging a dimension onto another dimension in the Data pane will create a hierarchy, which is a way of organizing data into different levels of detail, not groups9

Explanation

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

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

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

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

Explanation

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

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

Extracts are advantageous for several reasons:

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

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

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

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

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

By default, both field names are present in the Union, but contain several null values!

When field names in the union do not match, fields in the union contain null values. You can merge the non-matching fields into a single field using the merge option to remove the null values. When you use the merge option, the original fields are replaced by a new field that displays the first non-null value for each row in the non-matching fields.

You can also create your own calculation or, if possible, modify the underlying data to combine the non-matching fields.

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."

Table Description automatically generated

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

Table Description automatically generated

Now suppose a fourth table, "August2016", is added to the underlying data. Instead of the standard "Customer" field name, it contains an abbreviated version called "Cust."

Table Description automatically generated

Table Description automatically generated

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.

The View Data window displays as much of the data as possible by default, up to 10,000 rows. This can be increased though, if you wish to.

Read more:

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.

From the official Tableau documentation:

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

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.

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

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

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

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

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

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:

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:

Explanation

We need to use the concept of Groups for this question. Follow along:

1) First, Drag State to the Rows shelf, and Total Expenses to the Text Mark on the Marks Shelf:

2) Now, remove the SUM aggregation from Total Expenses, and add a quick table calculation -> Percent of total:

3) Next, Select the States of New York, California and Washington -> And then click the paperclip icon:

We can see the answer already : 23.386% in the view above (even before grouping!)

4) Finally, we get the following view and our answer:

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

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

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

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

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

Read more about stories in Tableau:

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

Explanation

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!

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!

Explanation

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

Graphical user interface, chart, line chart Description automatically generated

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.

Graphical user interface, application Description automatically generated

Explanation

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

As a general best practice, your pie chart should contain 2 to 5 categories. Anything more than that is not easy for the eyes to distinguish. This is a common question and mentioned in Tableau's own eLearning module as well!

See how to build a pie chart:

Explanation

Pretty common question on the Tableau Desktop Specialist exam.

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

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

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

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

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

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

To apply bold text formatting to rows or columns independently in Tableau, you should use the Rows tab or the Columns tab on the Format Font pane. This approach provides control over the formatting of text within individual rows or columns. By selecting the appropriate tab (Rows or Columns), you can apply formatting settings, including bold text, to only the selected rows or columns. This is a crucial feature for enhancing the readability and visual appeal of specific parts of a Tableau worksheet, allowing for emphasis on particular data points or categories.

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

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

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

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

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

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

Explanation

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.

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

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

Graphical user interface Description automatically generatedGraphical user interface, application, Word Description automatically generated

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

Graphical user interface, application Description automatically generated

Graphical user interface, application, Word 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.

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.

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:

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

For relational data sources, dates and times are automatically placed in the Dimensions area of the Data pane and are identified by the date or date-time icon. For example, the Order Date and Ship Date dimensions from an Excel data source are shown below:

When you place a relational date on a shelf, the field name is automatically modified to reflect the default date level. Tableau defines the default date level to be the level at which there are multiple instances. For example, if the date field includes multiple years, the default level is year. However, if the date field contains data for just one year but includes multiple months, then the default level is month.

Explanation

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

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)

Explanation

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

The following are the steps to import a CSV file:

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

2) Choose the appropriate file, and click Open:

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

Tree maps size begins from maximum in top left to smallest in bottom right.

See below to learn how to create a TreeMap and add colours to it:

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.

According to the official Tableau documentation:

According to the official documentation, the following are the requirements for using relationships:

1) When relating tables, the fields that define the relationships must have the same data type. Changing the data type in the Data Source page does not change this requirement. Tableau will still use the data type in the underlying database for queries.

2) You can't define relationships based on geographic fields.

3) Circular relationships aren't supported in the data model.

4) You can't edit relationships in a published data source.

5) You can't define relationships between published data sources.

6) Your workbook must use an embedded data source for you to be able to edit relationships and performance options in the Data Source page in Tableau Online or Tableau Server.

It is very much possible to specify the formatting at a WORKBOOK level (all sheets) instead of a single worksheet level.

You can quickly change how fonts, titles, and lines look in every view in a workbook by specifying format settings at the workbook level, instead of the worksheet level.

For example, you might want to use a specific font, size, and color so that all views adhere to your company's brand. You might also want to remove grid lines from your views—or make them more noticeable by increasing their pixel size or color.

You can also change the theme used by your workbook. Themes control items like the default font, colors, and line thickness. When you create a new workbook, it automatically uses the Default theme, which uses visual best practices.

Change fonts in your workbook:

You can change all fonts in your workbook or you can change fonts for only certain areas, such as just worksheet titles.

1) On the Format menu, select Workbook.

2) The Format Workbook pane replaces the Data pane on the left and provides a series of drop-down lists where you can change all font settings in a workbook, as well as the font settings for titles of worksheets, stories, and dashboards.

Note: If you have made font changes at the worksheet level, such as on a filter card or a worksheet title, changing the font at the WORKBOOK level will overwrite those changes.

Reset a workbook to its default settings

When you make changes to your workbook's font settings, a gray dot appears next to the setting in the Format Workbook pane. You can quickly switch back to default settings using the Reset to Defaults button.

1) On the Format menu, select Workbook.

2) In the Format Workbook pane, click Reset to Defaults.

Graphical user interface, application Description automatically generated

To create a trend line, we need:

Graphical user interface, application Description automatically generated

**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:

Explanation

Bin are a user-defined grouping of numerical data in the data source.

According to the official Tableau documentation: It's sometimes useful to convert a continuous measure (or a numeric dimension) into bins.

Have a look at the following image. When we right click a measure, we get the following options:

However, for a dimension (this is because the DATA TYPE of this dimension is a string:

But what if we have a dimension of type NUMBER (NUMERIC DIMENSION)? See below:

We can clearly create bins from dimensions too - they just have to be numeric :)

For more information, please refer to : 

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.)

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