TDS-C01 Questions and Answers

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

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:

Explanation

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

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

To create an alias:

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

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

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

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

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

Explanation

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

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

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

To set the default properties of a field to Currency in Tableau, you need to configure the number format of the field from the Data pane. This can be done by right-clicking the field in the Data pane and selecting Default Properties, then choosing the appropriate number format (in this case, Currency).

To perform a union in Tableau, the tables must have a related field with matching data types, and they must have the same number of fields. This allows the tables to be appended vertically in the data source. Different names or tables from different connections do not affect the ability to union the tables.

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Tables that you drag to the logical layer of the Data Source page canvas must be related to each other. When you drag additional tables to the logical layer canvas, Tableau automatically attempts to create the relationship based on existing key constraints and matching fields to define the relationship. If it can't determine the matching fields, you will need to select them.

If no constraints are detected, a Many-to-many relationship is created and referential integrity is set to Some records match. These default settings are a safe choice and provide the most a lot of flexibility for your data source.

According to the official documentation:

Joins are a more static way to combine data. Joins must be defined between physical tables up front, before analysis, and can’t be changed without impacting all sheets using that data source. Joined tables are always merged into a single table. As a result, sometimes joined data is missing unmatched values, or duplicates aggregated values.

Joins -

1) Are displayed with Venn diagram icons between physical tables

2) Require you to select join types and join clauses

3) Joined physical tables are merged into a single logical table with a fixed combination of data

4) May drop unmatched measure values

5) May duplicate aggregate values when fields are at different levels of detail

6) Support scenarios that require a single table of data, such as extract filters and aggregation

Explanation

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

To reach the correct answer, follow the steps below:

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

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

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

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.

Distribution Pane

Explanation

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

Explanation

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

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Explanation

Pretty common question on the Tableau Desktop Specialist exam.

1) First, lets create Sheet 1. For this, drag sport to the Row shelf, and Weight to the Text mark in the Marks shelf. Change its aggregation to Average:

2) Now, for sheet 2 - Drag nationality to the view, and gold to the size mark in the Marks shelf.

NOTE: Depending on your version of Tableau , you may need to assign a Geographical role to the nationality column first as follows:

3) Now, let's create a dashboard, and use both these sheets in it:

4) Now, for the most Important step, use SHEET 2 AS A FILTER FOR SHEET 1 as follows:

Now simply click on Russia in Sheet 2, and Sheet 1 will automatically update as follows:

Dates in Tableau will behave differently depending on whether they are a Datepart (blue) or a Datevalue (green). This affects how the axes display/behave and also how visualisations such as line charts will display. The difference essentially boils down to Dateparts behaving like a dimension as opposed to a measure which is how Datevalues behave. This means that Dateparts behave like discrete categories on the view whereas Datevalues are more like continuous numeric values.

Dateparts are discrete and they behave the same as dimension filters. If all dates are used on the filter then each individual date will be a datepart that can be selected/excluded. This is the same for each level of date, if datepart months is placed on filters January to December will be tick-able options in the filter. This also means that conditions and top/bottom filters can be applied to datepart filters like any other dimension filter.

Datevalues placed on filters behave like measure filters. A min and a max date can be set and there is a relative dates option which allows you to choose things like only show the previous 3 months or years etc.

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

Explanation

For relational data sources, dates and times are automatically placed in the Dimensions area of the Data pane and are identified by the date or date-time icon. For example, the Order Date and Ship Date dimensions from an Excel data source are shown below:

When you place a relational date on a shelf, the field name is automatically modified to reflect the default date level. Tableau defines the default date level to be the level at which there are multiple instances. For example, if the date field includes multiple years, the default level is year. However, if the date field contains data for just one year but includes multiple months, then the default level is month.

Explanation

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

Create a .twbx with file-based data sources

1) Select File > Save As.

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

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

4) Click Save.

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

The following files are included in packaged workbooks:

--> Background images

--> Custom geocoding

--> Custom shapes

--> Local cube files

--> Microsoft Access files

--> Microsoft Excel files

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

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

Explanation

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.

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.

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

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!

By default, both field names are present in the Union, but contain several null values!

When field names in the union do not match, fields in the union contain null values. You can merge the non-matching fields into a single field using the merge option to remove the null values. When you use the merge option, the original fields are replaced by a new field that displays the first non-null value for each row in the non-matching fields.

You can also create your own calculation or, if possible, modify the underlying data to combine the non-matching fields.

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."

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

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Now suppose a fourth table, "August2016", is added to the underlying data. Instead of the standard "Customer" field name, it contains an abbreviated version called "Cust."

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Data blending is performed on a sheet-by-sheet basis and is established when a field from a second data source is used in the view. To create a blend in a workbook already connected to at least two data sources, bring a field from one data source to the sheet—it becomes the primary data source.

Switch to the other data source and use a field on the same sheet—it becomes a secondary data source. An orange linking icon will appear in the data pane, indicating which field(s) are being used to blend the data sources.

According to the official Tableau Documentation:

To read more about Data Blending, click on THIS link.

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

We can very much blend multiple measures into a single axis. Such charts are called Combined-Axis / Blended-Axis charts. Follow along:

Measures can share a single axis so that all the marks are shown in a single pane. To blend multiple measures, drag one measure or axis and drop it onto an existing axis.

Instead of adding rows and columns to the view, when you blend measures there is a single row or column and all of the values for each measure is shown along one continuous axis. For example, the view below shows quarterly sales and profit on a shared axis.

Note: If you drag a measure on to the canvas and only see a single ruler indicator instead of the double ruler indicator shown below, Tableau creates dual axes instead of a blended axis. For more information about how to create dual axes, see Compare two measures using dual axes.

Explanation

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

 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.

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

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."

Your Tableau Desktop Specialist exam will be based on the 2020.1 version.

Set controls are a new feature introduced in the 2020.2 version, and hence is the correct answer - it is not a part of 2020.1

For the 2020.1 version the new features were:

1) Viz animations:

Viz animations help you see and understand your changing data. It’s easy to track the logical steps behind data’s evolution and tell powerful data stories. Sorting, filtering, adding fields, and other actions will now smoothly animate your visualizations. Choose whether to turn Viz Animations on or off, and decide how you’d best like to apply animations to your new workbooks.

2) Dynamic Parameters:

Say goodbye to republishing workbooks with parameters every time the underlying data changes. Set your parameter once, and Tableau will automatically update the parameter’s list of values every time someone opens the workbook.

3) Buffer Calculations:

Buffer calculations allow you to visualize the distance around point locations. Give Tableau three parameters—location, distance, and a unit of measure—and a buffer, or boundary is instantly created. Answering complex spatial questions becomes easier than ever before—visualize what properties are within 200 meters of a proposed transit site, or how many competitors’ stores are within 1 mile of their store, and more.

To add totals to a view using the Analytics pane:

Also, you can add totals from the Analytics tab in the Menu above:

This is a tricky question. We are talking about story POINTS, and not entire stories in the question.

To create a story, lets say I have a blank story with 1 dashboard and 1 worksheet.

I can simply drag the dashboard into the view to create a new story point.

Now, if I try to adjust the worksheet beside it in this same view, I cannot. See below:

The only option available is to replace the existing view. Therefore, the answer is NO since they both cannot be added.

Read more about stories in Tableau: https://help.tableau.com/current/pro/desktop/en-us/story_create.htm

Standard deviation is an aggregation that is available without requiring a table calculation or calculated field. Standard deviation is a statistical measure that shows how much variation there is from the average value in a set of data. Standard deviation is one of the predefined aggregations in Tableau that can be applied to any measure by selecting it from the context menu of the measure or from the drop-down menu on the Marks card6 The other options are not aggregations that are available without requiring a table calculation or calculated field. Running total, sample covariance, and percent of total are all examples of table calculations, which are computations that are applied to the values in an entire table or partition of a table. Table calculations can be created by selecting them from the context menu of a measure or by using functions in a calculated field7

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.

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.

 You can use the Color legend to access options to change a dimension’s color palette, in addition to the Marks card. The Color legend shows the colors assigned to each member of the dimension in the view. You can right-click on the Color legend and select Edit Colors to open the Edit Colors dialog box, where you can change the color palette, assign specific colors to dimension members, or edit the color transparency and border6 The other options are not valid ways to change a dimension’s color palette. Edit in Shelf is a feature that allows you to edit the fields on the Rows or Columns shelves by typing directly on the shelf. It does not affect the color palette of the dimension7 The Format menu allows you to change the appearance of various elements in the workbook, such as fonts, borders, shading, alignment, etc. It does not have options for changing the color palette of the dimension8 Edit Caption is a feature that allows you to add or edit a caption for a worksheet or dashboard. It does not affect the color palette of the dimension

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

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

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

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

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

To assign a geographic role to a field:

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

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

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

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.

There are three benefits of using an extract as compared to a live connection to a data source:

• A live connection to a data source can be slow due to network and user traffic, whereas a connection to an extract improves performance. An extract is a snapshot of data that is stored locally on your computer or on Tableau Server. An extract can reduce the load on the data source and speed up queries.
• Extracts are stored in memory (RAM), resulting in faster query performance as compared with live data connections. When you use an extract, Tableau loads the data into memory and optimizes it for analysis. This allows Tableau to perform calculations and aggregations faster than with live connections.
• Calculated fields perform better in workbooks connected to extracts than in workbooks with live connections to a data source. Calculated fields are custom fields that you create using formulas or expressions. When you use an extract, Tableau can process calculated fields more efficiently than with live connections.

You can combine two sets to compare the members. When you combine sets you create a new set containing either the combination of all members, just the members that exist in both, or members that exist in one set but not the other.

Combining sets allows you to answer complex questions and compare cohorts of your data. For example, to determine the percentage of customers who purchased both last year and this year, you can combine two sets containing the customers from each year and return only the customers that exist in both sets.

To combine two sets, they must be based on the same dimensions. That is, you can combine a set containing the top customers with another set containing the customers that purchased last year. However, you cannot combine the top customers set with a top products set.

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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.

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.

According to the Tableau Help, there are two filter modes for continuous filters: Range of Values and Single Value. The help also states that “Range of Values lets you specify a minimum and maximum value for the filter using sliders or input fields” and “Single Value lets you select one value on a slider for the filter” (page 1).

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:

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

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 :

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

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.

Explanation

When using a Blend, the primary data source appears with a BLUE tick-mark and the secondary data source appears with a ORANGE tick-mark.

See below:

Explanation

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

To add a reference line:

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

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

Explanation

Follow along to reach the correct answer:

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

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

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

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

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

Explanation

Follow the steps to get the correct answer : January 2018

• We are talking about dates, so use the Time series sheet as follows:
• Next, the following should be your view and clearly, January 2018 is the lowest point:

Read more about dates: https://interworks.com/blog/rcurtis/2017/01/30/tableau-deep-dive-dates-introduction-dates/

Explanation

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

All are correct, except - Copy of any local file-based data. This is contained in a .tdsx file (Tableau Packaged Data Source)!

According to the official documentation -

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, 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.

Padding lets you precisely space items on dashboard, while borders and background colors let you visually highlight them. Inner padding sets the spacing between item contents and the perimeter of the border and background color; outer padding provides additional spacing beyond the border and background color.

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

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

Explanation

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

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

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

Hierarchies in Tableau allow users to drill up and down to explore data at different levels of detail. By setting up a hierarchy, users can navigate through levels of the hierarchy to analyze data at each level, from the highest summary down to the finest detail.

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:

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

According to the Tableau Desktop Specialist Exam Guide, when using quick table calculations, such as Percent Difference From, that use a value in the previous column, the first data value in the visualization will be null, because there is no previous value to compare with.

Explanation

To reach the correct answer, follow these steps:

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

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

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

The following will be the final view:

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

THEREFORE,

2012 = 4,888

2011 -> 2014 = 17,817

Remember that dragging a discrete value to colour creates distinct colours for each item whereas dragging a continuous value to colour creates a gradient. ( Same for Map )

From the official documentation:

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

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

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

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:

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

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

For example -

THIS IS A VERY IMPORTANT QUESTION

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

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

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

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

An example:

It is very much possible to specify the formatting at a WORKBOOK level (all sheets) instead of a single worksheet level.

You can quickly change how fonts, titles, and lines look in every view in a workbook by specifying format settings at the workbook level, instead of the worksheet level.

For example, you might want to use a specific font, size, and color so that all views adhere to your company's brand. You might also want to remove grid lines from your views—or make them more noticeable by increasing their pixel size or color.

You can also change the theme used by your workbook. Themes control items like the default font, colors, and line thickness. When you create a new workbook, it automatically uses the Default theme, which uses visual best practices.

Change fonts in your workbook:

You can change all fonts in your workbook or you can change fonts for only certain areas, such as just worksheet titles.

1) On the Format menu, select Workbook.

2) The Format Workbook pane replaces the Data pane on the left and provides a series of drop-down lists where you can change all font settings in a workbook, as well as the font settings for titles of worksheets, stories, and dashboards.

Note: If you have made font changes at the worksheet level, such as on a filter card or a worksheet title, changing the font at the WORKBOOK level will overwrite those changes.

Reset a workbook to its default settings

When you make changes to your workbook's font settings, a gray dot appears next to the setting in the Format Workbook pane. You can quickly switch back to default settings using the Reset to Defaults button.

1) On the Format menu, select Workbook.

2) In the Format Workbook pane, click Reset to Defaults.

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To create a trend line, we need:

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Explanation

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

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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.

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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:

To access bolding options for the text in a tooltip in Tableau, you can:

• Select Tooltip on the Marks card, which allows you to edit the tooltip for the specific marks.
• Select Worksheet on the menu, and then Tooltip, to open the tooltip editor for the worksheet.
• Right-click on the Field and select Format, which lets you format the text including bolding options in the tooltip.

**IMPORTANT QUESTION AND EXPLANATION, PLEASE READ**

3 ways to group data -

1) Marks

2) Labels

3) Dimensions shelf.

*IMPORTANT*

If we Group the data by selecting the marks, then they remain separate marks in the view and then have the same colour. Also, a new group is created in the Dimensions shelf. Example -

Using the sample superstore dataset, first plot a bar chart showing sales for each sub-category:

Here, if we Select Phones, Chairs and Storage by selecting the MARKS (Bars), and then group them:

They remain seperate marks (BARS) but are grouped by the same colour.

Now, if we didn't do this, and rather grouped by selecting their Labels (Names):

Then they no longer remain separate Marks (bars) but are rather consolidated into a single Bar:

Finally, we can group directly from the Dimensions shelf as follows:

Now choose Phones, Chairs and Storage and Click Group:

You will now automatically have a new Dimension as follows:

Explanation

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

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

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

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:

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

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

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Explanation

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

Further,

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

Tableau Data Extract (TDE) is a snapshot of the data that Tableau stores locally. Good for very large datasets of which we only need few fields. Performance is optimised because it queries its own database engine instead of the local data source.

When you create an extract of your data, you can reduce the total amount of data by using filters and configuring other limits. After you create an extract, you can refresh it with data from the original data. When refreshing the data, you have the option to either do a full refresh, which replaces all of the contents in the extract, or you can do an incremental refresh, which only adds rows that are new since the previous refresh.

Extracts are advantageous for several reasons:

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

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

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

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

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