Desktop-Specialist Sample Questions Answers

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

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.

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According to the official Tableau documentation:

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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.

Hierarchies in Tableau are used to define a drill-down path through your data. By creating a hierarchy, you can organize related fields together, which makes it easier to navigate complex data models. This also allows users to explore data at different levels of detail, from the highest level of the hierarchy to the most granular details, simply by clicking to expand and collapse levels of the hierarchy in the view.

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.

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).

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.

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

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

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.

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.

 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

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.

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.

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.

Explanation

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

Explanation

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

Create a .twbx with file-based data sources

1) Select File > Save As.

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

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

4) Click Save.

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

The following files are included in packaged workbooks:

--> Background images

--> Custom geocoding

--> Custom shapes

--> Local cube files

--> Microsoft Access files

--> Microsoft Excel files

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

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

Explanation

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.

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

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

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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 :

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 -

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

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.

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.

Therefore, we need at least 2 measures for creating bullet graphs.

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

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 card5 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 card5 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 card5

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

Explanation

The data that you analyze in Tableau is often made up of a collection of tables that are related by specific fields (that is, columns). Joining is a method for combining data on based on those common fields. The result of combining data using a join is a virtual table that is typically extended horizontally by adding columns of data.

For example, consider the following two tables originating from a single data source:

We can combine these 2 tables, simply by joining the tables on ID to answer questions like, "How much was paid in royalties for authors from a given publisher?". By combining tables using a join, you can view and use related data from different tables in your analysis.

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 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.

Explanation

One way to view a measure in Tableau Desktop is to split it into bins. You can think of bins as buckets based on a range of values. For example, say you have a measure that represents age. Instead of aggregating the measure to calculate the average age, you can bin the measure to define age groups: 0–5, 6–10, 11–15, and so on. Then you can count the number of people in each age group.

Create a calculated field for variable bin size

Step 1

Select Analysis > Create Calculated Field.

Step 2

In the Calculated Field dialog box, complete the following steps:

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.

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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 )

Explanation

By default, all filters that you set in Tableau are computed independently. That is, each filter accesses all rows in your data source without regard to other filters. However, you can set one or more categorical filters as context filters for the view. You can think of a context filter as being an independent filter. Any other filters that you set are defined as dependent filters because they process only the data that passes through the context filter.

You may create a context filter to:

1) Improve performance – If you set a lot of filters or have a large data source, the queries can be slow. You can set one or more context filters to improve performance.

2) Create a dependent numerical or top N filter – You can set a context filter to include only the data of interest, and then set a numerical or a top N filter.

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".

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

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

Dimensions contain qualitative values (such as names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view.

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

View Data allows you to inspect your data in a spreadsheet-like layout. You can view data either for the data source as a whole, or to see the underlying data for an individual mark or a group of marks. In a worksheet, the rows that you see in the View Data window are always scoped to the current selection or the current view.

The View Data window displays as much of the data as possible by default, up to 10,000 rows. Field names are shown as column headers and can be dragged and dropped to change their display order. Click a column header to sort the values in that column.

From the official website:

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!

In fact, the opposite of this is true.

Trick : Whenever you think of joins -> Think that after the join is created, we get 1 single flat combined (joined) table. This flat combined table is created prior to us creating our visualizations. This happens at the physical layer.

If you ever think about relationships, know that all tables will remain distinct and separate, and relationships sit at the logical layer. At run time, when you bring in the dimensions and measures to create your viz, Tableau very smartly creates the necessary joins, relates the tables and sends queries to these tables to get the resultant data back in the most meaningful way possible. This allows you to focus on using your data and revealing insights from it and focus less on the data preparation aspect!

Refer to logical layer vs physical layer from the official documentation: https://help.tableau.com/current/server/en-us/datasource_datamodel.htm

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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.

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

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/

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.

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.

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.

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.

Unioning is the correct answer!

From the official documentation:

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."

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.

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

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

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

Of course! Follow along:

Right click on any measure, and choose Discrete as shown:

Once you do this, the green pill becomes blue in colour, indicating that it is now Discrete!

Explanation

The following is the official documentation for the String function LEFT:

In Tableau, parameters are dynamic values that can replace a constant in calculations, filters, and reference lines. If you have a parameter controlling a calculation, changing the parameter value can change the results of that calculation, thus impacting the visualization. Parameters can also be used to switch between different fields in the visualization; for example, allowing users to choose which measure or dimension to display.

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

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

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.

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.

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

According to the official Tableau documentation:

An example of an area chart is shown below:

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

In Tableau, when creating a combined axis chart, after dragging the first measure to the Rows shelf, you should drag the second measure directly onto the existing axis in the view. This will combine both measures on the same axis, allowing them to share a scale and an axis, which is the essence of a combined axis chart.

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!

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:

Measure Names is a dimension. Latitude, Longitude, and Number of records are all measures.

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

Important question! If you selected Dimension and Measure, don't worry! It is a very common mistake. But we're here to learn aren't we?

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.

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

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Had the question asked us to place this pill on the Rows shelf instead, we would've gotten a different answer:

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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

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

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

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

Explanation

For a manual sort, no matter how the data changes, the values will always stay in the sort order you kept stuff in.

From the official website:

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.

When dealing with a union of two tables in Tableau, using logical tables with a single table extract is the most appropriate approach. Logical tables allow for the integration of data from multiple tables in a way that is seamless and efficient for analysis. By using a single table extract, Tableau consolidates the data from the union into one extract, optimizing performance and enabling faster data processing. This approach is particularly beneficial when working with large datasets or complex unions.

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.

**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

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

AND

Explanation

When using a Percent difference, Tableau calculates what the percent change has occured as compared to the last data value. BUT, for the first data value, there is no previous value to compare it to. Hence, it appears as NULL.

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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.

Presently, there is no official way to connect your data in Firebase directly with Tableau Desktop.

A workaround however can be to export your Firebase data into Google BigQuery, and then connect it to Tableau Desktop.

But then again, it is a workaround and not an official out-of-the-box solution.

The following are the available Data sources available as of now:

1) Server

2) File

Explanation

In a box and whisker plot:

1) The ends of the box are the upper and lower quartiles, so the box spans the interquartile range

2) The median is marked by a vertical line inside the box

3) The whiskers are the two lines outside the box that extend to the highest and lowest observations.

Explanation

It is possible in Tableau to use a sheet within a story directly.

Moreover, in Tableau, a story is a sequence of visualizations that work together to convey information. You can create stories to tell a data narrative, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case.

At the same time, a story is also a collection of sheets, arranged in a sequence. Each individual sheet in a story is called a story point.

Explanation

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

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

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

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.

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.

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

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

 ( Simple Scatter Plot)

 (Matrix of Scatter Plots)

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

To create a scatter plot, follow the steps below:

From the official Tableau documentation:

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

To visually group marks in Tableau, you typically start by selecting the marks directly in the view. Once the desired marks are selected, you can then create a group from them. This will visually group the selected marks, as indicated by the blue color in the example provided.

Explanation

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

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

To combine data from another database with an existing data source in Tableau, the first step is to add a new connection. This will allow you to access the additional database and either blend or join the data from the two sources depending on your analysis needs.

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