Tableau TDS-C01 Tableau Desktop Specialist Exam Practice Test

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:

The option to create bins in Tableau is available for numeric fields. Bins allow you to group a series of numeric values into larger segments, which can simplify analysis and help in creating histograms or other visualizations that show the distribution of data. For example, you can create bins to group ages into categories like 0-10, 11-20, etc.

Explanation

Extracts are saved subsets of data that you can use to improve performance or to take advantage of Tableau functionality not available or supported in your original data. 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.

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

You can change the device layout of a dashboard by using the Dashboard pane or the Dashboard menu. The Dashboard pane allows you to select a device type and customize the layout for that device. The Dashboard menu allows you to create a new device layout or copy an existing one. The Format menu and the Layout pane do not have options for changing the device layout1

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

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

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

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

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

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

References:

Tableau's official documentation on dashboard objects: Dashboard Objects

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

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

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

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

1) Simultaneous animations

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

2) Sequential animations

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

To Animate visualizations in a workbook:

1) Choose Format > Animations.

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

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

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

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

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.

Continuous fields in Tableau have specific characteristics:

A. Continuous fields appear as green pills:

Continuous fields in Tableau are represented as green pills in the view. This indicates that they are treated as a continuous range of values rather than discrete categories.

B. Continuous fields are numeric:

Continuous fields typically consist of numeric data that can take any value within a range. They are used to measure and compare data values.

C. The values in continuous fields are treated as an infinite range:

Continuous fields are treated as an infinite range, allowing for detailed and granular analysis of data. Unlike discrete fields, which are considered distinct and separate, continuous fields are seen as a seamless continuum.

Incorrect options:

D. Continuous fields are categorical: This is incorrect because categorical fields are discrete, not continuous.

E. Only measures can appear as continuous: This is incorrect because dimensions can also be treated as continuous in certain contexts.

References:

Tableau's official documentation on continuous and discrete fields: Continuous and Discrete

From the official documentation:

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

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

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

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

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

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

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:

Top of Form

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

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

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

Bottom of Form

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

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

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

Graphical user interface, application Description automatically generated

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

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

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

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:

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

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: https://help.tableau.com/current/pro/desktop/en-gb/inspectdata_viewdata.htm

Explanation

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

The Data pane includes:

Dimension fields – Fields that contain qualitative values (such as names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view. Examples of dimensions include dates, customer names, and customer segments.

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

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

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

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

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

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

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

According to the official Tableau documentation:

Explanation

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

Follow along:

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

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

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

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

And Voila! We have our answer as follows:

iv) Last, drag Sales to Label:

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.

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

According to the official Tableau documentation:

An example of an area chart is shown below:

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.

Explanation

Yes, it is very much possible to use measures in the same view multiple times. For example, refer to the image below:

We are using BOTH the Sum of the revenue and the AVG of the revenue in the same view!

 You can use the Color legend to access options to change a dimension’s color palette, in addition to the Marks card. The Color legend shows the colors assigned to each member of the dimension in the view. You can right-click on the Color legend and select Edit Colors to open the Edit Colors dialog box, where you can change the color palette, assign specific colors to dimension members, or edit the color transparency and border6 The other options are not valid ways to change a dimension’s color palette. Edit in Shelf is a feature that allows you to edit the fields on the Rows or Columns shelves by typing directly on the shelf. It does not affect the color palette of the dimension7 The Format menu allows you to change the appearance of various elements in the workbook, such as fonts, borders, shading, alignment, etc. It does not have options for changing the color palette of the dimension8 Edit Caption is a feature that allows you to add or edit a caption for a worksheet or dashboard. It does not affect the color palette of the dimension

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

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

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:

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

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

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

Explanation

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.

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).

A bullet graph is a variation of a bar graph developed to replace dashboard gauges and meters. A bullet graph is useful for comparing the performance of a primary measure to one or more other measures. Below is a single bullet graph showing how actual sales compared to estimated sales.

We can create a Bullet graph with just 2 measures! This method requires the LEAST number of fields possible to create this type of chart.

The best way to tackle such questions in the exam is to click the "SHOW ME" button on top right, and hover over the chart we want to create.

In our case, it is a Bullet graph.

Therefore, we need 2 measures at least to create this chart, and 0 or more dimensions.

When we create a reference line, we get the following 3 options for the scope:

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

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.

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:

According to the Tableau Desktop Specialist Exam Guide, when using quick table calculations, such as Percent Difference From, that use a value in the previous column, the first data value in the visualization will be null, because there is no previous value to compare with.

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:

Dimensions don't have aggregation properties, and adding properties manually each time defeats the whole DEFAULT aggregation purpose. Window tab doesn't have any default aggregation option!

Data blending is performed on a sheet-by-sheet basis and is established when a field from a second data source is used in the view. To create a blend in a workbook already connected to at least two data sources, bring a field from one data source to the sheet—it becomes the primary data source.

Switch to the other data source and use a field on the same sheet—it becomes a secondary data source. An orange linking icon will appear in the data pane, indicating which field(s) are being used to blend the data sources.

According to the official Tableau Documentation:

To read more about Data Blending, click on THIS link.

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

When you drop a discrete field on Color in the Marks card, Tableau displays a categorical palette and assigns a color to each value of the field.

When you drop a continuous field on Color, Tableau displays a quantitative legend with a continuous range of colors.

Web version:

Desktop Version:

For more information about color palettes, see Color Palettes and Effects.

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.

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.

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

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

Stacked bar charts will usually have lesser number of bars compared to a normal bar chart:

Normal bar chart - 9 bars

Stacked Bar Chart - 3 bars

We can easily see a 'part-of-a-whole' methodology being used here as well - we are seeing the breakdown of Segments within each Category.

To easily visualize trends over time - This is the definition of a line chart.

To visualize each discrete category using a separate bar - This can be accomplished using a simple bar chart, why use a stacked one?

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'

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.

According to Tableau's official documentation:

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.

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

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

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

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

Explanation

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

When you connect to a data source, Tableau automatically separates date fields into hierarchies so you can easily break down the viz. You can also create your own custom hierarchies. For example, if you have a set of fields named Region, State, and County, you can create a hierarchy from these fields so that you can quickly drill down between levels in the viz.

To set the default properties of a field to Currency in Tableau, you need to configure the number format of the field from the Data pane. This can be done by right-clicking the field in the Data pane and selecting Default Properties, then choosing the appropriate number format (in this case, Currency).

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

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:

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

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

Clearly, Regex Match is not one of these options!

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

Graphical user interface, application Description automatically generated

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

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

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

**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

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:

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.

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.

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!

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 access bolding options for the text in a tooltip in Tableau, you can:

Select Tooltip on the Marks card, which allows you to edit the tooltip for the specific marks.

Select Worksheet on the menu, and then Tooltip, to open the tooltip editor for the worksheet.

Right-click on the Field and select Format, which lets you format the text including bolding options in the tooltip.

Explanation

By default, measures placed in a view are aggregated by SUM, which means that the data for that field in all of the rows is combined. Measures can also be aggregated as average, median, count, or count distinct.

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

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

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

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

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

When you click the icon to the right of Air Ticketing Cabin Type Name, the highlighter toggles on or off. The highlighter is a feature that allows you to highlight marks in the view that match a specific value or condition. You can access the highlighter by clicking the icon next to a dimension or measure in the legend, filter, or parameter. The icon looks like a light bulb with a plus sign. When you click the icon, a highlighter box will appear where you can enter or select a value to highlight. The marks that match the value will be highlighted in the view, while the others will be dimmed. You can also use the highlighter box to search for values, clear the highlighting, or lock the highlighting. To turn off the highlighter, you can click the icon again or close the highlighter box. The other options are not correct descriptions of what occurs when you click the icon to the right of Air Ticketing Cabin Type Name. The filter options do not open, because the icon is not for filtering, but for highlighting. The legend does not toggle on or off, because the icon is not for showing or hiding the legend, but for accessing the highlighter. The Edit Colors dialog box does not open, because the icon is not for changing the colors of marks, but for highlighting them.

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.

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.

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

According to the official Tableau documentation:

Depending on the version the extract was created in, Tableau extract files can have either the .hyper or .tde file extension. Extract files are a local copy of a subset or entire data set that you can use to share data with others, when you need to work offline, and improve performance. For more information, see Extract Your Data.

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

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

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:

Explanation

Joins combine tables by adding more columns of data across similar row structures. This can cause data loss or duplication if tables are at different levels of detail, and joined data sources must be fixed before analysis can begin.

Inner join

Left Join

Blends, unlike relationships or joins, never truly combine the data. Instead, blends query each data source independently, the results are aggregated to the appropriate level, then the results are presented visually together in the view.

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.

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:

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

Graphical user interface Description automatically generated

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:

Graphical user interface Description automatically generated with low confidence

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

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!

Tables that you drag to the logical layer of the Data Source page canvas must be related to each other. When you drag additional tables to the logical layer canvas, Tableau automatically attempts to create the relationship based on existing key constraints and matching fields to define the relationship. If it can't determine the matching fields, you will need to select them.

If no constraints are detected, a Many-to-many relationship is created and referential integrity is set to Some records match. These default settings are a safe choice and provide the most a lot of flexibility for your data source.

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.

The only incorrect option is - It is mandatory to combine sheets when using Tableau.

All others are valid advantages that Dashboards provide when using Tableau!

To create a packaged data source (.tdsx file) in Tableau, you would right-click on the data connection in the Data pane and select the option to add it to saved data sources. This action packages the data source with the metadata that you've defined in Tableau, such as calculations, groups, and sets, so that you can easily share it with others. This does not package the data itself, which is a separate step if you're working with local file-based data.

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

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.

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

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

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

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

According to the official Tableau documentation: