TDS-C01 Exam Dumps - Tableau Desktop Specialist

When exporting a view as an image in Tableau, the default export includes everything that is currently displayed in the view, with Tableau applying its own styling, including fonts. The default format for an exported image is PNG, which is a raster-based file format that captures all visual elements as pixels. PNG is widely used for its lossless compression and is suitable for detailed images like those produced by Tableau. Unlike vector-based images, PNGs do not embed fonts, and the image quality remains consistent when the image is viewed on different platforms, which makes it ideal for inserting into documents like Microsoft Word.

Explanation

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

Follow the steps below:

Treemaps use automatically generated sizes that cannot be resized by using the Marks card. A treemap is a type of visualization that shows hierarchical data as a set of nested rectangles. Each rectangle represents a dimension member and its size is proportional to a measure value. Tableau automatically calculates the size of each rectangle based on an optimal aspect ratio for readability and comparison. You cannot manually adjust the size of each rectangle by using the Marks card or any other option in Tableau10 The other chart types do not use automatically generated sizes that cannot be resized by using the Marks card. Pie charts use angles to show proportions of a whole, not sizes. Histograms use bins and frequencies to show distributions of a measure, not sizes. Area charts use filled areas to show trends over time or categories, not sizes. You can adjust the size of these chart types by using the Marks card or other options in Tableau

To apply bold text formatting to rows or columns independently in Tableau, you should use the Rows tab or the Columns tab on the Format Font pane. This approach provides control over the formatting of text within individual rows or columns. By selecting the appropriate tab (Rows or Columns), you can apply formatting settings, including bold text, to only the selected rows or columns. This is a crucial feature for enhancing the readability and visual appeal of specific parts of a Tableau worksheet, allowing for emphasis on particular data points or categories.

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

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 you click Salt Lake City in the view, the URL action will direct you to https://en.wikipedia.org/wiki/Salt+Lake+City+Car+Dropoff+City. A URL action is a hyperlink that points to a web page 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 URLs3 In this case, the URL action uses https://en.wikipedia.org/wiki/ as the URL target, where is a field value from the view. When you click Salt Lake City in the view, Tableau will replace with Salt Lake City in the URL target. However, since spaces are not allowed in URLs, Tableau will encode them as + signs instead. Therefore, the final URL will be https://en.wikipedia.org/wiki/Salt+Lake+City+Car+Dropoff+City 3 The other options are not correct because they do not reflect how Tableau encodes field values in URL actions.

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

Clearly, Regex Match is not one of these options!

According to the official Tableau documentation:

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

Explanation

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

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:

In Tableau, a Density map (also known as a heat map) uses automatically generated sizes for the data points that cannot be resized by using the Marks card. This chart type is designed to display density of data points on a map, where the size and color of the data points represent the concentration of data in that area.

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.

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.

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 Tableau's official documentation:

*Very important question*

If we select the labels in the view and then group, a new consolidated mark is created - in our case bar since we are talking about a bar chart in the question. See below:

Then on grouping, a new bar is created, and the colour of all bars remain the same.

Had we grouped by choosing the marks instead of the labels, the following would be the result:

Explanation

GDP / Population = GDP Per Capita

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

As a general best practice, your pie chart should contain 2 to 5 categories. Anything more than that is not easy for the eyes to distinguish. This is a common question and mentioned in Tableau's own eLearning module as well!

See how to build a pie chart:

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

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."

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!

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!

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

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:

Distribution Pane

Explanation

This is the Analytics pane! Read more from the official documentation below:

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

Explanation

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.

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

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/

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.

The Marks Card allows us not only to edit the Shape, Text and Colour, but also to modify the Tooltip and the level of detail of the visualisation!

The Marks card is a key element for visual analysis in Tableau. As you drag fields to different properties in the Marks card, you add context and detail to the marks in the view.

You use the Marks card to set the mark type (see Change the Type of Mark in the View), and to encode your data with color, size, shape, text, and detail. To change the mark settings, see Control the Appearance of Marks in the View.

In this example, three different fields have been dragged to different properties in the Marks card. Segment is on Color, Region is on Shape, and Quantity is on Size.

After you add a field to the Marks card, you can click the icon next to the field to change the property it is using. You can also click the property buttons in the Marks card to change those settings.

Many properties can have multiple fields. For example, you can add multiple fields to Label, Detail, Tooltip, and Color. Size and Shape can only have one field at a time. For more details, see Control the Appearance of Marks in the View.

You can use Wildcard Search to set up search criteria to automatically include tables in your union. Use the wildcard character, which is an asterisk (*), to match a sequence or pattern of characters in the Excel workbook and worksheet names, Google Sheets workbook and worksheet names, text file names, JSON file names, .pdf file names, and database table names.

When working with Excel, text file data, JSON file, .pdf file data, you can also use this method to union files across folders, and worksheets across workbooks. Search is scoped to the selected connection. The connection and the tables available in a connection are shown on the left pane of the Data source page.

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.

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

Explanation

If you answered this question quickly and correctly, you're well prepared for the exam! Most students stumble while creating a Dual axis chart, so go ahead and give yourself a pat on the back!

To create a dual axis chart for the problem mentioned:

1) Drag Product Type to the column shelf, and Sales and Profit to the Row shelf:

2) Now, to focus on 2013, drag Date to the filter shelf and select only 2013:

3) Now, click on the Profit pill in the Rows Shelf, and select dual axis:

4) Now, in the marks shelf, choose Sales, and change the chart type to bar. Similarly, for Profit, change the chart type to Line.

Now the chart looks like this:

Now we change the Profit chart type to line:

5) Finally, we synchronise the axis as follows: Right click on the axis, and choose 'Synchronise axis'

And, our final view and answer is:

By default, measures placed in a view are aggregated. Mostly you'll notice that the aggregation is SUM, but not ALWAYS.

The type of aggregation applied varies depending on the context of the view.

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:

From the official Tableau documentation:

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.

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:

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

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.

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.

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

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:

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

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?

Bar charts in Tableau do not require a dimension to be created. You can create a bar chart using only a measure; this will produce a single bar that represents the aggregate of the measure values, such as the sum or average of sales.

Tree maps size begins from maximum in top left to smallest in bottom right.

See below to learn how to create a TreeMap and add colours to it:

Explanation

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.

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

Yes, it is possible to create worksheet-specific filters in Tableau.

When you add a filter to a worksheet, by default it applies to the current worksheet. Sometimes, however, you might want to apply the filter to other worksheets in the workbook.

Then, you can select specific worksheets to apply the filter to or apply it globally to all worksheets that use the same data source or related data sources.

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:

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

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!

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

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

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

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

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

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

Upon doing this, we get the correct answer as : 

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

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

**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:

 A dual axis chart is useful for comparing two measures that have different scales. A dual axis chart is a type of visualization that shows two measures using two independent axes layered on top of one another. A dual axis chart allows you to compare and contrast two measures that have different ranges or units of measurement, such as sales and profit margin, temperature and precipitation, or population and GDP per capita. A dual axis chart can also show different mark types for each measure, such as bars and lines, circles and areas, or shapes and texts. The other options are not valid reasons for using a dual axis chart for comparing two measures. Have little in common is not correct, because a dual axis chart is meant to show some kind of relationship or correlation between two measures, not just contrast them. Are Table Calculations is not correct, because a dual axis chart can be used with any type of measure, whether it is an aggregation, a calculation, or an expression. Are aggregated Dimensions is not correct, because a dual axis chart cannot be used with dimensions, only with measures. Dimensions are fields that contain qualitative values that are used to categorize or segment data, not compare them.

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/

To display multiple distinct lines on the same axis based on a field, you should place the field on the Color shelf in the Marks card. This will encode each distinct value in the Region field with a different color, resulting in separate lines for each region on the same axis.

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.

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 :

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.

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.

According to the official Tableau documentation:

Explanation

You can add a reference line to any continuous axis in the view.

To add a reference line:

Drag Reference Line from the Analytics pane into the view. Tableau shows the possible destinations. The range of choices varies depending on the type of item and the current view.

In a simple case, the drop target area offers three options:

The 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

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).

Of course! As an example, see below:

1) Using the Sample Superstore data, let's plot a bar chart showing the Sales for each Category:

Observe that we have 3 marks - Each bar in a bar chart is called a mark. Similarly, each point in a scatter plot is also a mark , and so on for all charts.

1 row by 3 columns means that clearly on the y-axis (Sales), we have only a single mark - a single continous axis, but 3 different marks (Technology, Furniture and Office supplies ) on the x-axis.

2) Now let's add subcategory to the view as well (another dimension):

Observe that the number of marks has increased - i.e the number of Bars.

Also, notice we now have 1 row and 17 columns. Simply because 1 row = Sales (on the y-axis), and on the x-axis, we have 17 different columns (i.e product sub categories!!)

You can adjust the size for all charts except the Tree Map. You use dimensions to define the structure of the treemap, and measures to define the size or color of the individual rectangles. Treemaps are a relatively simple data visualization that can provide insight in a visually attractive format.

In a Tree Map, the measure itself defines the size and colour! The greater the sum of Measure for each category, the darker and larger its box.

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.

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

In Tableau, you can rename a field directly in the Data pane by clicking and holding on the field name until it becomes editable, allowing you to type a new name. Alternatively, you can use the drop-down menu associated with the field in the Data pane and select the "Rename" option. Both methods provide a quick and easy way to change the name of a field without affecting the underlying data structure. The "Format menu" and "Replace References" option do not apply to renaming fields.

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.

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

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.

When creating a group by selecting headers in a Tableau view, the newly created grouped dimension replaces the original dimension field on either the Rows or Columns shelf. This grouping action aggregates the selected headers into a single group, and this new group dimension is automatically placed in the view, replacing the original dimension. This functionality allows for more simplified and customized categorization within the data visualization, enhancing the ability to analyze and interpret data according to specific groupings.

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

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.

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!

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

Graphical user interface, application Description automatically generated

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

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

Explanation

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

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

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

2) Navigate to a new worksheet.

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

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

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

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

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

The visualization updates to look like this:

Apply the quick table calculation

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

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

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

Important question! You cannot use a context filter to replace a data source filter since each filter type has its own use case. Also, a content filter is an Independent filter and all other filters are called dependent since they only process the data that passes through a context filter.

According to the official documentation : 

Explanation

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:

Explanation

It is possible to join a maximum of 32 tables in Tableau!

Two use cases for creating hierarchies from the Data pane are to add drilldown functionality for fields and to organize related fields together. 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. By creating hierarchies from the Data pane, you can quickly drill down or up in a hierarchy to add or subtract more levels of detail in the view. You can also use hierarchies to group related fields together in the Data pane, making it easier to find and use them14 The other options are not valid use cases for creating hierarchies from the Data pane. To concatenate all fields into a single field, you need to use a calculated field or a join, not a hierarchy. To create faster-performing queries, you need to optimize your data source, filters, calculations, or extracts, not create hierarchies

Explanation

Here's how to add image files to your repository:

1) Find image file on the internet. I try to find consistent image formats if I plan to use a set of shapes such as logos or flags.

2) Download the image to your computer.

3) Drag images into your My Documents -> My Tableau repository -> Shapes folder.

4) Open Tableau and your new shapes will automatically be included in your "edit shapes" menu.

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

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

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.

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

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

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

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

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

Explanation

To reach the correct answer, follow these steps:

1) You can simply drag Country to the view, and look at the marks in the bottom left of Tableau Desktop - 147 marks!

2) Or, you can simply go to Data Source -> Country Tab -> Describe

As you can see, 147 members exist in this Country column!

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: