Desktop-Specialist Tableau Desktop Specialist Exam Questions and Answers

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

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.

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.

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.

Explanation

The word 'static tool' gives it away.

According to the official website :

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.

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.

When users connect to Tableau, the data fields in their data set are automatically assigned a role and a type.

Role can be of the following two types:

1) Dimension

2) Measure

Type can be of the following :

1) String

2) Number

3) Geographic

4) Boolean

5) Date

6) Date and Time

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

Clearly, Regex Match is not one of these options!

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:

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

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

GDP / Population = GDP Per Capita

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

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.

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.

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.

Explanation

As the question mentions, we need to create a SET with the following conditions -> Choose only those customers whose Sales > 30,000

1) Right click on customer name --> Create --> Set

2) Let's Name the Set - Customer>30k ( you can name it anything you want :) )

Select USE ALL, and then move to the CONDITION TAB:

3) In the Condition Tab, Choose BY FIELD -> Select Sales -> Sum -> Greater than 30000 , and click OK

4) You should now have a new Set in the Data Pane as follows:

5) Drag this set to the rows shelf, and click on SHOW MEMBERS IN SET. Now drag Sales to the Column Shelf.

6) Click on the Show Mark Labels, and Sort ascending icons as shown:

7) Voila! We have our answer:

c

Explanation

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!

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

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.

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

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 card4 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 data5 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 stars6 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 view7 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 view8

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

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

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:

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

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.

With dimension filters in Tableau, you can use several filter modes, including "Multiple Values (drop-down)" which allows users to select one or more values from a drop-down list of all the dimension's members. Another mode is "Wildcard Match," which lets users filter the view by typing in a text box to match dimension members that contain the typed string. These filter types are particularly useful for string or categorical dimensions where users need to search or select specific members to display in the view.

Explanation

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

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

Explanation

Follow along to get the correct answer:

• Drag Country to the view, and then Patents to the Size Mark on the Marks shelf as follows :

2) But, this isn't all right? We need to focus on the year 2013. This can be done by using the year column as it is (continuous) in the filter shelf, or by converting it to discrete first and then using it:

2.1 As it is (continuous)

2.2 Converting to discrete first & then using it

and then :

3) We can now see that France, with 485 has the 2nd most number of patents for the year 2013

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.

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.

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.

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

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:

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

Explanation

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.

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

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

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

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

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:

In Tableau, when you initially add a measure to the rows shelf, you create one mark in the view that represents the aggregate value of that measure. When you then add a dimension with 11 members to the columns shelf, the view is subdivided into 11 separate marks, each representing the measure for one of the dimension members. This results in a total of 11 marks in the view after the dimension is added, one for each member of the dimension.

When creating a date filter in Tableau, anchor refers to the date in a relative-date filter to which you anchor a unit of time. A relative-date filter is a type of filter that allows you to dynamically filter data based on a range of time relative to the current date or a specific date. For example, you can use a relative-date filter to show data for the last 7 days, the next 3 months, or the current quarter1 To create a relative-date filter, you need to specify the following options: The date field that you want to filter. The unit of time that you want to use for the filter, such as days, weeks, months, quarters, or years. The range of time that you want to show relative to the anchor date, such as last, next, this, or to date. The anchor date that you want to use as the reference point for the filter. You can use the current date or a custom date as the anchor date1 For example, if you want to create a relative-date filter that shows data for the last 3 months from January 1st, 2022, you would select the following options: Date field: Order Date Unit of time: Months Range of time: Last 3 Anchor date: Custom (01/01/2022) 1 The other options are not valid definitions of anchor when creating a date filter in Tableau. The mid-point in the range of displayed dates is not related to the anchor date, but rather to the center of the axis that represents the date field. The date in a range-of-dates filter to which you anchor units of time is not correct, because a range-of-dates filter does not use an anchor date, but rather a start and end date that can be fixed or dynamic. The latest date in the data source that can be found is not related to the anchor date, but rather to the maximum value of the date field in the data source2

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.

According to the official Tableau documentation:

An example of an area chart is shown below:

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

As the names suggest, if we subtract the order date from the shipping date, we simply get the number of days between these 2 dates.

We can these use this calculated field in our charts, and can use COUNT, SUM, AVG etc with them according to our need.

Explanation

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/

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.

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

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

Explanation

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

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

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

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

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

1) Simultaneous animations

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

2) Sequential animations

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

To Animate visualizations in a workbook:

1) Choose Format > Animations.

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

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

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

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

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

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

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).

According to the [Tableau Desktop Specialist Exam Guide], a join is a way to combine table columns in relational databases by using shared values. A join can be inner, left, right, or full, depending on how the matching rows are included or excluded.

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:

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:

Explanation

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

Graphical user interface, chart, line chart Description automatically generated

To align the two axes in a dual axes chart to use the same scale, right-click (control-click on Mac) the secondary axis, and select Synchronize Axis. This aligns the scale of the secondary axis to the scale of the primary axis.

In this example, the Sales axis is the secondary axis and the Profit axis is the primary axis.

If you would like to change which axis is the primary, and which axis is the secondary, select the field on the Columns or Rows shelf that is the secondary, and drag it in front of the primary field on the shelf until you see an orange triangle appear.

In this example, you can select the SUM(Sales) field on the Rows shelf, and drag it in front of the SUM(Profit) field. The Sales axis is now the primary and the Profit axis is the secondary.

Graphical user interface, application Description automatically generated

Explanation

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

Create a calculated field for variable bin size

Step 1

Select Analysis > Create Calculated Field.

Step 2

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

Explanation

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.

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

According to Tableau's official documentation:

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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:

An example of an area chart is shown below:

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.

In Tableau, to create a reference line, one of the axes in the view must contain an aggregated measure. Reference lines are typically used to add context or additional information to the data in a view, and they are often based on some form of aggregate such as the average, median, sum, etc., of a measure.

Explanation

THIS IS A VERY IMPORTANT QUESTION

To answer this question, you need to understand Tableau's Order of Operations. See below and remember this always:

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

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

Graphical user interface, chart Description automatically generated

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.

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:

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Explanation

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

Follow along:

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

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

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

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

And Voila! We have our answer as follows:

iv) Last, drag Sales to Label:

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 (Option stating - To create a dependent filter eliminated here). 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.

For example, suppose you’re in charge of breakfast products for a large grocery chain. Your task is to find the top 10 breakfast products by profitability for all stores. If the data source is very large, you can set a context filter to include only breakfast products. Then you can create a top 10 filter by profit as a dependent filter, which would process only the data that passes through the context filter.

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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:

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

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

Explanation

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?

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

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

Extracts are advantageous for several reasons:

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

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

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

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

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

To work with the MOST up-do-date data, use a live connection instead!

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

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.

Chart, line chart Description automatically generated

Explanation

To reach the correct answer, follow the steps below:

1) Drag Category, and sub-category to the row shelf. Drag Profit to the Column shelf

2) Click the Sort-ascending icon as shown above, to sort the profits from least to greatest as shown:

Click the 'Show mark labels icon'

As we can see, Fasteners has the least Profit in the Office Supplies Category, and hence is our correct answer!

Three statements that accurately describe dimensions are: Contain qualitative values Affect the level of detail in the view Can be continuous or discrete Dimensions are fields that contain qualitative values, such as names, dates, or geographical data. You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view by creating headers or labels for marks or by defining how data is partitioned for table calculations. Dimensions can be continuous or discrete depending on their data type and format. Continuous dimensions are those that have an infinite range of possible values, such as numbers or ratios. Discrete dimensions are those that have a finite number of distinct values, such as names, categories, or dates3 The other options are not accurate statements about dimensions. Contain numeric, quantitative values is not correct, because fields that contain numeric, quantitative values are measures, not dimensions. Measures are fields that contain numeric values that you can measure and aggregate. Affect the formatting options in the view is not correct, because formatting options are not determined by dimensions, but rather by user preferences and choices. Formatting options allow you to change the appearance of various elements in the workbook, such as fonts, borders, shading, alignment, etc3

Explanation

You can show trend lines in a visualization to highlight trends in your data.

To add trend lines to a view, both axes must contain a field that can be interpreted as a number. For example, you cannot add a trend line to a view that has the Product Category dimension, which contains strings, on the Columns shelf and the Profit measure on the Rows shelf.

However, you can add a trend line to a view of sales over time because both sales and time can be interpreted as numeric values.

Explanation

A Pareto chart is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the ascending cumulative total is represented by the line.

On the primary axis, bars are used to show the raw quantities for each dimension member, sorted in descending order.

On the secondary axis, a line graph is used to show the cumulative total in percent format.

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

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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

Chart, bar chart Description automatically generated

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