Desktop-Specialist Tableau Desktop Specialist Exam Questions and Answers

This is a tricky question often asked in the exam.

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

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

Graphical user interface, chart, bar chart Description automatically generated with medium confidence

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

Graphical user interface, text, application Description automatically generated

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

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

Remember that joins are defined in the physical layer and relationships in the logical layer.

You can still specify joins between tables in the physical layer of a data source. Double-click a logical table to go to the Join/Union canvas in the physical layer and add joins or unions.

Every top-level, logical table contains at least one physical table. Open a logical table to view, edit, or create joins between its physical tables. Right-click a logical table, and then click  Open . Or, just double-click the table to open it.

When you create a data source, it has two layers. The top-level layer is the logical layer of the data source. You combine data between tables in the logical layer using relationships.

The next layer is the physical layer of the data source. You combine data between tables at the physical layer using joins. For more information, see  Logical and physical tables in the data model

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:

Explanation

Tableau SERVER enables us to create workbooks and views, dashboards, and data sources in Tableau Desktop, and then publish this content to our own server.

Moreover, as a Tableau Server administrator you will control who has access to server content to help protect sensitive data. Administrators can set user permissions on projects, workbooks, views, and data sources.

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:

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 -

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!

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 types 2

Yes! We get different options for filtering depending on whether we use a  categorical  data (think dimension) or  quantitative  data (think measure).

Important Note : Each tab adds additional definitions to your filter. For example, you can select to exclude values under the General tab, and also add limits under the Top tab. Selections and configurations from both tabs are applied to your filter. At any time, you can see the definitions of your filter under Summary on the General tab.

Note:  If you have a large data source, filtering measures can lead to a significant degradation in performance. It is sometimes much more efficient to filter by creating a set containing the measure and then apply a filter to the set. For more information about creating sets, see  Create Sets

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 :

According to the official Tableau documentation:

Graphical user interface, text, application Description automatically generated

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.

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!

THIS IS A VERY IMPORTANT QUESTION

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

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

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

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

An example:

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

Tableau will automatically create a hierarchy for date and geographic data. A hierarchy is a way of organizing data into different levels of detail. For example, a date hierarchy can have year, quarter, month, and day levels. A geographic hierarchy can have country, state, city, and zip code levels. Tableau recognizes date and geographic data based on their data types and formats, and creates hierarchies for them by default.  Tableau does not automatically create hierarchies for date & time or string data 3

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

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

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.

According to the official Tableau documentation:

Tableau data source files have the .tds file extension. Data source files are shortcuts for quickly connecting to the original data that you use often. 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. For more information, see Save Data Sources.

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.

When using a data source that has relationships, you can add a join between two or more tables by dragging a table directly on top of an existing logical table from the Tables pane. This will create a logical table that contains the joined tables.  You can then edit the join type, join clauses, and join calculation as needed 2  The other options are not valid ways to add a join between tables when using relationships. From the Tables pane, double-clicking a table will add it to the data source as a separate logical table, not joined with any other table. From the Connections pane, selecting Add will allow you to add another connection to the data source, not join tables within the same connection.  Double-clicking a logical table in the canvas will open the Data Source page, where you can view and edit the fields in the logical table, not join it with another table 2

Explanation

Follow along to reach the correct answer:

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

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

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

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

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

Explanation

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.)

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.

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.

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.

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).

Measure names and values  CANNOT  be deleted in Tableau like other columns can. These are auto-generated.

Calculated Fields, and Number of records can both be deleted.

Explanation

Follow along:

1) Drag Assortment and Year ID (choose Discrete Month) to Columns shelf, and Sales to the Columns Shelf.

For sales, click on the pill - > choose Quick Table calculation - > Year over Year growth.

The view should now look like:

It is clear that October with -55.3% had the lowest Year on Year growth.

This is one of the most common questions on the Tableau Desktop Specialist Exam.

Wrong options -

1) Don ' t use backgrounds -  This is not a solution. What if we want to use backgrounds? We can ' t just stop using backgrounds to solve this problem.

2) Decrease the font size -  Do you think using a smaller font will make the text more readable? No right? Hence, this is wrong too.

All other options are ways recommended to make your text more readable!

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

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.

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.

Explanation

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

Graphical user interface Description automatically generated

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

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.

**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:

Using the Sample superstore as a reference:

1) Let ' s plot a bar chart showing SUM(Quantity) for each Segment:

2) Right click on the x-axis (Segment):

Notice we don ' t have an option to edit the axis, only header. This is because only continous values form the AXIS.

3) Similarly, right click on the y-axis (Quantity):

Now we have the option to edit BOTH the axis and the header.

Explanation

GDP / Population = GDP Per Capita

Here Sum is a function, / and + are operators. On the bottom there are comments.

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

This is true. a  Manual   Sort  lets you select a value and move it to the desired position, either by dragging it in the list or using the arrows to the right.

However, as soon as you choose some other type of sort - be it field, nested, or alphabetic, our custom created manual sort gets deleted/cleared.

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.

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?

Tableau Desktop will display marks by using a diverging palette as the default to display data that has both negative and positive quantitative values. A diverging palette is a type of color palette that uses two different color ranges to show positive and negative values. For example, a red-green diverging palette uses shades of red for negative values and shades of green for positive values.  A diverging palette is automatically applied when there are both negative and positive values for a measure that is placed on Color on the Marks card 5  The other options are not correct types of color palettes that Tableau Desktop uses as the default for data with both negative and positive values. A full color range is not a valid term for a color palette in Tableau. A sequential palette is a type of color palette that uses different shades of one color to show variations in a single measure.  A sequential palette is usually applied when there are only positive values for a measure that is placed on Color on the Marks card 5  A categorical palette is a type of color palette that uses different colors to show discrete values or categories.  A categorical palette is usually applied when there is a dimension that is placed on Color on the Marks card 5

Date values in Tableau represent specific points in time and are typically formatted in a standard date format.

Option A, " 2020-05-01 " , is a standard date format representing the 1st of May, 2020.

Option D, " January 1, 1995 " , is another example of a date value, representing the 1st of January, 1995. Options B ( " December " ) and C ( " Wednesday " ) represent a month and a day of the week, respectively, but do not specify a particular date.

Explanation

Follow along:

1) Drag Assortment and Year ID (choose Discrete Month) to Columns shelf, and Sales to the Columns Shelf.

For sales, click on the pill - > choose Quick Table calculation - >   Year over Year growth.

The view should now look like:

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).

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 :

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.

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:

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

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

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

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!

According to the [Tableau Desktop Specialist Exam Guide], an incremental refresh only adds rows that are new, based on a specified column and value. A full refresh replaces all the extracted data with the data in the underlying data source. A full refresh is usually very slow, especially for large extracts. An incremental refresh can take less time, depending on how many new rows are added. A full refresh does not need to be configured, it is the default option for extracts in Tableau. An incremental refresh can be run from both Tableau Desktop and Tableau Server.

In the context of Tableau, " Migrated Data " typically refers to data or workbooks that have been upgraded from a previous version of Tableau Desktop. When you open a workbook in a newer version of Tableau, the data sources within that workbook might be labeled as " Migrated Data, " indicating that they have undergone a conversion process to be compatible with the new version ' s features and architecture.

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.

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

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.

 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 border 6  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 dimension 7  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 dimension 8  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

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

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.

Beginning in version 10.5, when you create a new extract, it uses the  .hyper  format instead of the .tde format.

Extracts in the .hyper format take advantage of the improved data engine, which supports the same fast analytical and query performance as the data engine before it, but for  even larger extracts.

Although there are many benefits of using .hyper extracts, the primary benefits include the following:

1) Create larger extracts:  You can create extracts with billions of rows of data. Because .hyper extracts can support more data, you can consolidate .tde extracts that you previously had to create separately into a single .hyper extract.

2) Create and refresh extracts faster:  While Tableau has always optimized performance for creating and refreshing extracts, version 2020.3 supports faster extract creation and refreshes for even larger data sets.

3) Experience better performance when interacting with views that use extract data sources:  Although smaller extracts continue to perform efficiently, larger extracts perform more efficiently.

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 names 8  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 groups 9

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.

Explanation

This question is directly from the Official Tableau Desktop Specialist exam guide.

Since we are talking about the AVERAGE home values for the United States in 2016, the question is directly offering us a hint that the answer has something to do with aggregation and that too the values tell us that we ' re working with MEASURES.

Date part and Date values don ' t really make much sense given the question, and neither does geography.

Therefore, the answer naturally is " An aggregated measure " .

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

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

The Shape option is available for scatter plots and packed bubbles views. The Shape option allows you to change the shape of marks in the view by selecting from a predefined set of shapes or adding custom shapes.  You can access the Shape option by placing any field on Shape on the Marks card 4  Scatter plots are views that show the relationship between two numerical variables by plotting them as coordinates on a Cartesian plane. You can create a scatter plot by placing at least one measure on Columns and at least one measure on Rows on the Marks card.  You can then use Shape to assign different shapes to different categories or segments in your data 5  Packed bubbles are views that show hierarchical data as a set of nested circles. Each circle represents a dimension member and its size is proportional to a measure value. You can create a packed bubble chart by placing one or more dimensions on Detail and one measure on Size on the Marks card.  You can then use Shape to change the shape of circles to other shapes such as squares or stars 6  The other options are not valid views for using the Shape option. Side-by-side circles are views that show proportions of a whole by using circles with different angles and sizes arranged horizontally or vertically. You can create a side-by-side circle chart by placing one dimension on Columns or Rows and one measure on Angle and Size on the Marks card.  You cannot use Shape to change the shape of circles in this view 7  Heat maps are views that show the distribution of two or more measures by using a color gradient and size. You can create a heat map by placing one or more dimensions on Columns and Rows and two measures on Color and Size on the Marks card.  You cannot use Shape to change the shape of marks in this view 8

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

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.

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

You can assign an alias to a field member before creating a visualization. An alias is an alternative name that you can assign to a value in a dimension field. You can use aliases to rename specific values within a dimension to make them more relevant or descriptive in your view than what the original data provides.  For example, you can use aliases to shorten long names, correct spelling errors, or replace codes with meaningful labels 6  You can create aliases for the members of discrete dimensions only. They cannot be created for continuous dimensions, dates, or measures. To create an alias for a dimension member, you can right-click the dimension in the Data pane and select Aliases, then enter a new name for each member under Value (Alias). You can also create an alias by right-clicking a dimension member in the view and selecting Edit Alias.  You can do this before or after creating a visualization 6  The other options are not accurate statements about aliases. You cannot create an alias for a discrete measure, because measures are not discrete fields. You cannot create an alias for a continuous dimension, because aliases are only available for discrete dimensions. When you assign an alias, the name does not change in the database, only in Tableau.  Aliases are stored as part of the workbook or data source, and do not affect the original data 6

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

From the official documentation: 

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

1) Simultaneous animations

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

2) Sequential animations

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

To create a simple scatter plot in Tableau, you need to have a measure on Columns and a measure on Rows. A scatter plot is a type of visualization that shows the relationship between two numerical variables. In Tableau, you can create a scatter plot by placing at least one measure on the Columns shelf and at least one measure on the Rows shelf. The measures can be continuous or discrete, but they must be aggregated.  The marks in the scatter plot represent the intersection of the values for each measure 1  The other options are not valid ways to create a simple scatter plot in Tableau. A dimension on Detail and a measure on Columns will create a bar chart, not a scatter plot. A dimension on Columns and a measure on Rows will create a line chart or an area chart, depending on the mark type.  A dimension on Columns and a dimension on Rows will create a text table or a heat map, depending on the mark type 1

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.

Text Description automatically generated

Explanation

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

Follow the steps below:

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

Diagram Description automatically generated

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

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:

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.

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:

According to the official Tableau documentation:

An example of an area chart is shown below:

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.

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!

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.

The benefits of using a live connection over an extract include:

B: A live connection ensures that the data in the workbook is as up-to-date as the database itself, providing fresher data compared to a static extract which is updated at intervals.

C: A live connection queries the database server directly, which means it uses the server ' s memory and processing power rather than relying on the client computer ' s resources.

A live connection does not necessarily require less network overhead (A) as it may continually send queries over the network, and it is not always faster than an extract (D) because extracts can provide quicker response times for complex queries or large datasets.

Explanation

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 .

Explanation

VERY IMPORTANT QUESTION FOR THE EXAM, PAY ATTENTION

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

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

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

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

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

Click OK.

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

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

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

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

Clearly, Mexico has the highest Shipping Delay!

Explanation

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.