TDS-C01 Practice Exam Questions with Answers Tableau Desktop Specialist Certification

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.

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

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.

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

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.

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:

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

Graphical user interface Description automatically generated

Explanation

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

Explanation

Yes! We get different color palettes. They are:

*From the official Tableau documentation*

To change the color for a value

1) Click on an item on the left, under Select Data Item.

2) Click a new color in the palette on the right. In Tableau Desktop you can hover over a swatch to identify the color.

3) Repeat for as many values that you want to change.

4) In Tableau Desktop, click OK to exit the Edit Colors dialog box. In Tableau Server or Tableau Online, simply close the dialog box.

AND

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.

In Tableau, a Fixed Level of Detail (LOD) expression calculates values at a specific level of granularity, regardless of the dimensions in the view. The computation of a fixed LOD expression can be influenced by a context filter. A context filter serves as a primary filter, setting the context for the rest of the filters in the view. When a context filter is applied, it effectively changes the level at which the fixed LOD expression is computed, thereby affecting its outcome. Other types of filters, such as table calculation, measure, and dimension filters, do not have this influence on fixed LOD expressions.

You can drag the filter by clicking on the 2 lines on top, and then dragging the filter as shown:

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.

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

The word 'static tool' gives it away.

According to the official website :

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

The basic building blocks for a histogram are as follows:

Demo :

According to Tableau's official documentation:

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.

Using the Sample superstore as a reference, click on the manage metadata icon as follows:

We can rename a particular column name to make it easier to remember and use in Tableau. Let's change Order ID to oID as shown:

Now, we'll see oID when using this data source in Tableau. This WILL NOT affect the original data source. The remote field name let's us see what the name of the column is in the ORIGINAL Data source.

For Standard Deviation and Variance, we don't need to use quick table calculations, since they are available by default. See below:

However, as seen in the types of quick table calculations available in Tableau, Rank and Moving Average belong to only this category.

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:

A parameter is a global placeholder value such as a number, date, or string that can replace a constant value in a calculation, filter, or reference line.

For example, you may create a calculated field that returns True if Sales is greater than $500,000 and otherwise returns False. You can replace the constant value of “500000” in the formula with a parameter. Then, using the parameter control, you can dynamically change the threshold in your calculation.

For example -

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

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

The only incorrect option is - Click on Dashboard in the Menu bar, select Tooltip, and then use the italics option.

This option doesn't exist. See below:

The rest of the options do exist, and therefore are correct:

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.

Explanation

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

Please refer to the images below:

Explanation

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

For example, suppose you have the following customer purchase information stored in three tables, separated by month. The table names are "May2016," "June2016," and "July2016."

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

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

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.

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!

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!

Explanation

Follow along the steps below:

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

Explanation

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

If you chose 111,060 you were SO close to the correct answer but made a small mistake - you didn't change the aggregation to AVERAGE! This is one of the common mistakes many test takers make, so keep this in mind.

To reach the correct answer, follow the steps below:

1) Draw Assortment to the Column shelf, and drag Year to the Rows Shelf. Then Drill down further on Year to accomodate Quarters and Months as well!

Although this seems enough, DON'T FORGET to change the aggregation like in the next step, which will completely change the values!

The correct answer as you can see is 1,461 - Sales for Harware Assortment in 2017 Q4, October

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

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

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

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

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

A URL action is a hyperlink that points to a web page, file, or other web-based resource outside of Tableau. You can use URL actions to create an email or link to additional information about your data. To customize links based on your data, you can automatically enter field values as parameters in URLs.

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

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!

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.

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:

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

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

Explanation

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:

Top of Form

The correct answer is Toggle the highlighting ON/OFF. If selected, whichever value you choose from this legend will be highlighted in the view. However, if it is deselected, then even if you choose a value in the Legend, it will NOT be highlighted.

See below:

Chart, bar chart Description automatically generated

Bottom of Form

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.

*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:

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).

Explanation

Data is generated and analyzed at many different levels of granularity. Granularity is the level of detail of the data. For example, when looking at graduation data, granularity would describe whether a row in the data set represents a single person or the graduating class of a university.

It contains all the measures in your data, collected into a single field with continuous values - This is the definition for 'Measure Values'.

All others are True w.r.t. Measure Names!

The Measure Names field contains the names of all measures in your data, collected into a single field with discrete values.

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

To create a stacked bar chart in Tableau, you can drag a second dimension to the Color shelf on the Marks card. This action will segment the bars already present in the chart by the new dimension, stacking the segments on top of each other within each bar. This is a common method to add additional layers of detail to a bar chart and effectively compare parts to a whole across categories.

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

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).

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.

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

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

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

To assign a geographic role to a field:

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

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

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

Explanation

Measures contain numeric quantitative values hence that option is incorrect.

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

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

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:

The beauty of context filters is that according to Tableau's Order of Operations, they are executed before Sets.

This means that based on what Region's you've selected - Tableau will first only preserve the rows for those Regions. THEN, after this it will compute the Set , i.e , Bottom 10 products in each Region.

1) First let's create a set to compute the Bottom 10 Products by Profit.

2) Next, take region on the Rows Shelf followed by the Set we just created. Drag Region and the Set to the Filters Shelf as well.

3) Now, try to only visualize the data for the South Region:

4) The problem right now is that Tableau is computing the Set first (Bottom 10 Products), and then applying the Dimension Filter - South Region and hence these values are incorrect. Note how these aren't even 10 products, but rather just 8. To fix this, simply add Region to Context:

Upon doing this, we get the correct answer as : 

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

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

Only 1 option is correct -

Click on Dashboard in the Menu bar followed by Copy Image

Right click on the dashboard, and choose Copy, then image - Try doing this, you will end up copying just one of the worksheets not the entire dashboard

Click on Worksheet in the Menu bar followed by Export, then choose Image - Again, try doing this. You will end up copying just one of the worksheets not the entire dashboard

Using the floating export worksheet option on the Dashboard - No such option exists

Explanation

Yes! To concatenate fields, they must be of same data type. However, there is a workaround which we can use - Type casting. See below:

Here, State and City are Strings, but Postal Code? Nope. It's an Integer. So we can simply use the STR() function to convert it into a String, and hence the entire equation becomes valid!

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

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

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

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.

According to the official Tableau documentation:

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

Explanation

You don't need to know ANY programming language to use quick table calculations!

Follow along with the steps below to learn how to apply a quick table calculation to a visualization:

1) Open Tableau Desktop and connect to the Sample-Superstore data source, which comes with Tableau.

2) Navigate to a new worksheet.

3) From the Data pane, under Dimensions, drag Order Date to the Columns shelf.

4) From the Data pane, under Dimensions, drag State to the Rows shelf.

5) From the Data pane, under Measures, drag Sales to Text on the Marks Card.

6) From the Data pane, under Measures, drag Profit to Color on the Marks Card.

7) On the Marks card, click the Mark Type drop-down and select Square.

The visualization updates to look like this:

Apply the quick table calculation

1) On the Marks card, right-click SUM(Profit) and select Quick Table Calculation > Moving Average.

Note: You can only perform quick table calculations on measures in the view.

A delta symbol appears on the field to indicate that a quick table calculation is being applied to the field. The colors in the visualization update to show the moving average of profit across the years.

Explanation

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

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

To create an alias:

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

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

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

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

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

Explanation

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

By default, the shape that a Heap map uses is a "Square". See below:

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

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

2) Now you can show labels by:

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

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

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

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

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.

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

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

Explanation

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

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

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

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

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

The following is our visualisation:

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

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.

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

Explanation

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

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

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

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

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

Explanation

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

When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains. You use these fields to build views of your data.

Further,

The calculated field formula LEFT("Sales Data", 5) will correctly produce the output "Sales" from the string value "Sales Data". The LEFT function in Tableau returns the specified number of characters from the start of the string. Here, the first 5 characters of "Sales Data" are "Sales".

Explanation

To reach the correct answer, follow these steps:

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

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

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

The following will be the final view:

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

THEREFORE,

2012 = 4,888

2011 -> 2014 = 17,817

Explanation

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

1) Linear Trend Line

2) Logarithmic Trend Line

3) Exponential Trend Line

4) Polynomial Trend Line

5) Power Model

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

See the following image:

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

Explanation

If you chose 2, then you were very close but probably didn't plot the actual Percent Difference on your view. ( One of the marks is just over the line).

Firstly, Drop the Week ID onto the column shelf, and convert it to continuous since we need both Year and Quarter as mentioned in the question.

2) Next, Drop assortment to filters shelf so that we can focus on Electronics!

3) This should be your view now. Click on the Show Mark Labels icon as shown:

The final view is as follows, with 3 points below 0 ( i.e negative )

When creating a histogram in Tableau, bin size refers to the range of the continuous measure counted in each bin. A histogram is a chart that displays the shape of a distribution of a continuous measure. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins. The basic building blocks for a histogram are as follows: Mark type: Automatic; Rows shelf: Continuous measure (aggregated by Count or Count Distinct); Columns shelf: Bin (continuous or discrete)4 To create bins from a continuous measure, you need to specify the size of bins, which determines how many bins are created and how wide they are. The size of bins is equal to the difference between consecutive values along the axis that represents the bins. For example, if you have bins with values 0-10, 10-20, 20-30, etc., then the size of bins is 10. You can either enter a value for the size of bins manually or have Tableau suggest an optimal bin size based on a formula that considers the number of distinct rows and the minimum and maximum values in the data5 The other options are not valid definitions of bin size when creating a histogram in Tableau. The minimum number of axis ticks in the view is determined by Tableau’s automatic scaling and formatting of axes, which can be adjusted manually if needed. The count distinct (COUNTD) of items on either axis is an aggregation function that returns the number of unique values in a field, which can be used as a measure in a histogram but not as bin size. The maximum number of marks in the view is limited by the performance and readability of the visualization, which can be improved by filtering, sorting, or aggregating the data4

According to the official Tableau documentation:

An example of an area chart is shown below: