Tableau TDS-C01 Tableau Desktop Specialist Exam Practice Test

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

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

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

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.

Explanation

After making changes to Data, we can save that new data source as a .tds file. To do so, go to data menu on top and then choose your current connected data source. Then next click on Add to Saved Data sources. This will save all calculated fields, changes to fields etc. It will be saved in My Tableau Repository -> Mydatasources. This will then also appear on Tableau Home Page under saved data sources like SampleSuperStore.

Note: Data source files do not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you've made on top of the actual data such as changing default properties, creating calculated fields, adding groups, and so on.

twb and .twbx are not the BEST solutions since the questions nowhere mentions that we need to store our workbooks as well.

twm is a bookmark which contains a single worksheet and are an easy way to quickly share your work.

Explanation

A bullet graph is a variation of a bar graph developed to replace dashboard gauges and meters. A bullet graph is useful for comparing the performance of a primary measure to one or more other measures.

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

According to the official Tableau documentation:

Dimensions don't have aggregation properties, and adding properties manually each time defeats the whole DEFAULT aggregation purpose. Window tab doesn't have any default aggregation option!

According to the official Tableau documentation:

An example of an area chart is shown below:

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.

From the official documentation, the following are the major advantages of using Tableau Data Extracts:

From Tableau 2020.2 onwards, .hyper is the recommended way since it is faster than .tde!

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

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

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

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

1) Server

2) File

Explanation

This is true, indeed!

The LEFT JOIN keyword returns all records from the left table (table1), and the matched records from the right table (table2). The result is NULL from the right side, if there is no match.

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 :

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.

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

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.

Explanation

Data is generated and analyzed at many different levels of granularity. Granularity is the level of detail of the data. For example, when looking at graduation data, granularity would describe whether a row in the data set represents a single person or the graduating class of a university.

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

You can use a story to present a data narrative to lead your audience to your conclusions, or to assemble a sequenced analysis to share with collaborators. A story is a sequence of visualizations that work together to convey information. You can create stories to tell a data story, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case4

Explanation

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

Explanation

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

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:

You should use a relationship instead of a join for two data sets when the data sets include similar data aggregated at different levels of detail. A relationship is a way of combining data from different tables based on common fields without creating a single table with all fields. A relationship allows you to query data from multiple tables as needed and preserve the level of detail of each table. A relationship is useful when you have data sets that are aggregated at different levels of detail, such as sales by region and sales by product. A relationship can match data from different levels of detail without creating null values or duplicate rows. The other options are not valid situations for using a relationship instead of a join for two data sets. The data sets include similar data aggregated up to the highest level is not correct, because a relationship is not needed when both data sets have the same level of detail. You can use either a relationship or a join in this case, depending on your preference and performance. The data sets are in two separate tables within a single spreadsheet is not correct, because a relationship is not limited by the location or format of the data sets. You can use a relationship to combine data from different sources or connections, such as databases, files, or web services. To use both data sets across multiple sheets in a visualization is not correct, because a relationship does not affect how you use data in your visualization. You can use either a relationship or a join to create multiple sheets and dashboards with your data sets.

According to the Tableau Help, headers are “labels that identify the different parts of your view”. The help also states that “Headers are created when you place a discrete dimension on Columns or Rows” (page 1).

Explanation

Line charts connect individual data points in a view. They provide a simple way to visualize a sequence of values and are useful when you want to see trends over time, or to forecast future values.

Please refer to the images below:

Explanation

A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.

According to the 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.

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.

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

The relative date filter can be used to select a range of dates relative to the current date, such as the past month, the current quarter, etc. This filter type dynamically adjusts the range based on the current system date, making it suitable for use with the TODAY() function.

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

a calculated field that has a formula of SUM(Sales)/SUM(Profit) is a measure, because it returns a numeric value that can be aggregated and used for analysis. A parameter is a user-defined variable that can be used in calculations or filters. A dimension is a categorical field that can be used to group or slice data. A set is a subset of data based on some condition.

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.

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.

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.

A Tableau story point is an individual container in a story that holds a sheet or dashboard. It's like a slide in a presentation, and a story is a sequence of these points that can be used to convey a data narrative, showing how facts are connected and guiding the audience through a sequence of analysis steps.

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.

Only 1 option is correct -

Click on Dashboard in the Menu bar followed by Copy Image

Right click on the dashboard, and choose Copy, then image - Try doing this, you will end up copying just one of the worksheets not the entire dashboard

Click on Worksheet in the Menu bar followed by Export, then choose Image - Again, try doing this. You will end up copying just one of the worksheets not the entire dashboard

Using the floating export worksheet option on the Dashboard - No such option exists

February is a discrete date part, because it is a specific value that can be used to group or filter data by month. 07Mar2017, 20Sep2016:9:8:8:6546, and 01/23/2021 are continuous date values, because they represent points along a continuous timeline that can be used for analysis.

When using a data source that has relationships, you can add a join between two or more tables by dragging a table directly on top of an existing logical table from the Tables pane. This will create a logical table that contains the joined tables. You can then edit the join type, join clauses, and join calculation as needed2 The other options are not valid ways to add a join between tables when using relationships. From the Tables pane, double-clicking a table will add it to the data source as a separate logical table, not joined with any other table. From the Connections pane, selecting Add will allow you to add another connection to the data source, not join tables within the same connection. Double-clicking a logical table in the canvas will open the Data Source page, where you can view and edit the fields in the logical table, not join it with another table2

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.

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:

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

Sets are custom fields that are created within Tableau Desktop based on dimensions from your data source. They are subsets of your data, which can be created manually or computed. Either dimensions or measures can be used to determine what is included or excluded from a set using conditional logic, but to CREATE a set we use dimensions.

Reference : https://interworks.com/blog/rcurtis/2016/10/26/tableau-deep-dive-sets-introduction-sets/

Explanation

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:

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.

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

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.

Explanation

Tricky options! Go to hyperlink and Go to Web page are not valid Actions in Tableau.

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.

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

Explanation

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

Using the Sample superstore as a reference:

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

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

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

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

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

An Individual Axis in Tableau is obtained by adding a continuous into Rows or Columns Shelf.

Example:

In order to show Individual Axis in Tableau First, we drag and drop the Color from Dimension shelf to Column Shelf. Next, we drag and drop the Sales Amount from measures shelf to Rows Shelf. Since it is a continuous value, the Sales Amount will be aggregated to default Sum. Once you drag them, following Chart report will be generated.

Next, we drag and Drop one more measure value, i.e., Total Product Cost from Measures Region to Rows Shelf. Because it is a Measure value, Total Product Cost is aggregated to default Sum. From the below screenshot, you can observe that Tableau has created an individual axis for each measure (continuous field).

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.

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

Explanation

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

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

Extracts are saved subsets of data that you can use to improve performance or to take advantage of Tableau functionality not available or supported in your original data. When you create an extract of your data, you can reduce the total amount of data by using filters and configuring other limits. After you create an extract, you can refresh it with data from the original data.

When refreshing the data, you have the option to either do a full refresh, which replaces all of the contents in the extract, or you can do an incremental refresh, which only adds rows that are new since the previous refresh.

Explanation

If you chose 2, then you were very close but probably didn't plot the actual Percent Difference on your view. ( One of the marks is just over the line).

Firstly, Drop the Week ID onto the column shelf, and convert it to continuous since we need both Year and Quarter as mentioned in the question.

2) Next, Drop assortment to filters shelf so that we can focus on Electronics!

3) This should be your view now. Click on the Show Mark Labels icon as shown:

The final view is as follows, with 3 points below 0 ( i.e negative )

Explanation

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

It is possible to join a maximum of 32 tables 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.

According to the official Tableau documentation:

Tableau data source files have the .tds file extension. Data source files are shortcuts for quickly connecting to the original data that you use often. Data source files do not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you've made on top of the actual data such as changing default properties, creating calculated fields, adding groups, and so on. For more information, see Save Data Sources.

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.

Explanation

The computer on which you are installing or upgrading Tableau Server must meet the minimum hardware requirements. If the Setup program determines that your computer does not meet the following requirements, you will not be able to install Tableau Server.

These minimum requirements are appropriate for a computer that you use for prototyping and testing of Tableau Server. They apply to single-node installations and to each computer in a distributed installation.

Explanation

To interactively display information from the web INSIDE a dashboard, you can use a URL action with a web page object.

For example, you might have a dashboard that shows profits by country. In addition to showing the profit data in your dashboard, you also want to display supplemental information about the countries from a web site.

In Tableau, the two elements that can have their values changed by using a dashboard action are Sets and Parameters. Dashboard actions can be configured to modify the values within a set or a parameter, allowing for interactive and dynamic changes in the visualization based on user interactions. For example, selecting a specific data point in a dashboard can trigger an action that updates a set or changes the value of a parameter, which in turn can alter the displayed data or the appearance of visualizations within the dashboard.

Explanation

When you track data in Excel spreadsheets, you create them with the human interface in mind. To make your spreadsheets easy to read, you might include things like titles, stacked headers, notes, maybe empty rows and columns to add white space, and you probably have multiple tabs of data too.

When you want to analyze this data in Tableau, these aesthetically pleasing attributes make it very difficult for Tableau to interpret your data. That’s where Data Interpreter can help.

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The correct answer is Toggle the highlighting ON/OFF. If selected, whichever value you choose from this legend will be highlighted in the view. However, if it is deselected, then even if you choose a value in the Legend, it will NOT be highlighted.

See below:

Chart, bar chart Description automatically generated

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

The View Data window displays as much of the data as possible by default, up to 10,000 rows. This can be increased though, if you wish to.

Read more: https://help.tableau.com/current/pro/desktop/en-gb/inspectdata_viewdata.htm

According to the Tableau Help, a highlight table is “a cross-tabulation that uses color to encode values”. The help also states that “Highlight tables use the Square mark type” (page 1).

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

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

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

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

Explanation

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

Explanation

The different aggregations available for a measure determine how the individual values are collected: they can be added (SUM), averaged (AVG), or set to the maximum (MAX) or minimum (MIN) value from the individual row values.

For a complete list of the available aggregations, check out - List of Predefined Aggregations in Tableau.

The level of detail is determined by the dimensions in your view—for information about the concept of level of detail, see How dimensions affect the level of detail in the view.

Disaggregating your data can be useful for analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.

Disaggregating data can be useful when you are viewing data as a scatter plot. See Example: Scatter Plots, Aggregation, and Granularity.

You should save a workbook as a PDF document if you need paper copies of the workbook. A PDF document preserves the layout and formatting of the workbook, and can be easily printed or shared. Saving a workbook as a PDF document is not necessary or useful in the other situations1

Explanation

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

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

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

Explanation

Yes! To concatenate fields, they must be of same data type. However, there is a workaround which we can use - Type casting. See below:

Here, State and City are Strings, but Postal Code? Nope. It's an Integer. So we can simply use the STR() function to convert it into a String, and hence the entire equation becomes valid!

The only incorrect option is - It is mandatory to combine sheets when using Tableau.

All others are valid advantages that Dashboards provide when using Tableau!

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!

According to the Tableau Desktop Specialist Exam Readiness, a line chart will be created whenever you place measures on one shelf, and a date dimension on the other. This is because Tableau automatically recognizes date fields and treats them as continuous dimensions.

Explanation

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

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

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

You can change the scope of a reference line by choosing one of the following options: Per Pane, Entire Table, or Per Cell. The scope determines how many reference lines are added to the view and how they are calculated. Per Pane adds one reference line for each pane in the view. Entire Table adds one reference line for the entire table in the view. Per Cell adds one reference line for each cell in the view

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

In Tableau, a Fixed Level of Detail (LOD) expression calculates values at a specific level of granularity, regardless of the dimensions in the view. The computation of a fixed LOD expression can be influenced by a context filter. A context filter serves as a primary filter, setting the context for the rest of the filters in the view. When a context filter is applied, it effectively changes the level at which the fixed LOD expression is computed, thereby affecting its outcome. Other types of filters, such as table calculation, measure, and dimension filters, do not have this influence on fixed LOD expressions.

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

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

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,

When the Physical Tables option is selected for an extract in Tableau, an individual table is created for each physical table in the extract. This means that the extract will include a separate table for each underlying table in your database, maintaining the database's structure within the extract. This can be useful when you need to preserve the original granularity of the data or when working with certain database optimizations.

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

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

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

Explanation

From the official Tableau website:

Explanation

Whenever we want to add actions to a Dashboard, we can trigger then in the following 3 ways:

1) Select

2) Hover

3) Menu

Hover is best for highlighting, select for filtering. Menu action is added to the tooltip and user can decide whether to run that action or not (best for URL actions)

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.

To clear all sorting in a Tableau visualization, you would go to the Worksheet menu, select the "Clear" option, and then choose "Sorts." This action removes all sorting that has been applied to the visualization, including any custom sorting or sorting based on multiple fields. This is a quick way to reset the view to its default sorting state and is particularly useful when you have applied various sorting layers and wish to start fresh.

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.

To create a simple scatter plot in Tableau, you need to have a measure on Columns and a measure on Rows. A scatter plot is a type of visualization that shows the relationship between two numerical variables. In Tableau, you can create a scatter plot by placing at least one measure on the Columns shelf and at least one measure on the Rows shelf. The measures can be continuous or discrete, but they must be aggregated. The marks in the scatter plot represent the intersection of the values for each measure1 The other options are not valid ways to create a simple scatter plot in Tableau. A dimension on Detail and a measure on Columns will create a bar chart, not a scatter plot. A dimension on Columns and a measure on Rows will create a line chart or an area chart, depending on the mark type. A dimension on Columns and a dimension on Rows will create a text table or a heat map, depending on the mark type1

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

To reach the correct answer, follow the steps below:

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

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

Click the 'Show mark labels icon'

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