TDS-C01 Tableau Desktop Specialist Questions and Answers

Explanation

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

The calculated field formula LEFT( " Sales Data " , 5) will correctly produce the output " Sales " from the string value " Sales Data " . The LEFT function in Tableau returns the specified number of characters from the start of the string. Here, the first 5 characters of " Sales Data " are " Sales " .

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

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 case 4

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.

All answers except November are examples of Date Values (continuous in nature).

See below:

You can see that the option in Green symbolizes our correct answer, i.e only a Month. In our case that month is November (the correct answer).

All other options are combinations  of a year with one other value  (like a month, quarter, or day). So this is how by looking at an option you can know if its a date part or date value!

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

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.

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.

Yes! We get different options for filtering depending on whether we use a  categorical  data (think dimension) or  quantitative  data (think measure).

Important Note : Each tab adds additional definitions to your filter. For example, you can select to exclude values under the General tab, and also add limits under the Top tab. Selections and configurations from both tabs are applied to your filter. At any time, you can see the definitions of your filter under Summary on the General tab.

Note:  If you have a large data source, filtering measures can lead to a significant degradation in performance. It is sometimes much more efficient to filter by creating a set containing the measure and then apply a filter to the set. For more information about creating sets, see  Create Sets

Explanation

When you connect to a 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.

You should use a union when you have two tables with similarly named columns of data that you want to combine. A union is a method for combining data by appending rows of one table onto another table.  The tables that you union must have the same number of fields, the same field names, and the same data types 2

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

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 )

Before you can build a view and analyze your data, you must first  connect  Tableau to your data. Tableau supports connecting to a wide variety of data, stored in a variety of places.

By default, when you connect a data source to Tableau, Tableau will create a live connection to the data.

Live connection refers to a data source that contains direct connection to underlying data, which provides real-time or near real-time data. With a live connection, Tableau makes queries directly against the database or other source, and returns the results of the query for use in a workbook. Users can create live connections and then share them on Tableau Server so that other Tableau users can use the same data using the same connection and filtering settings.

You can add reference lines, bands, distributions, or (in Tableau Desktop but not on the web) box plots to any continuous axis in the view.

Reference Lines - You can add a reference line at a constant or computed value on the axis. Computed values can be based on a specified field. You can also include confidence intervals with a reference line.

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 Tableau 10  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

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

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).

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.

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!

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

In a box and whisker plot:

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

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

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

Explanation

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

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

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 :

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 dates 3  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, etc 3

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.

In fact, the opposite of this is true.

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

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

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

From the official documentation:

When you have a view with a large amount of data you might want to explore your data interactively and  highlight a specific mark or group of marks while still maintaining the context of where those marks show in your view.

To do this you can turn on the Highlighter for one or more discrete fields that are included in your view and that affect the level of detail

Example -  Here we just want to focus on Public Affairs college dimension, but don ' t want to filter out or remove the rest of the data:

Note that filtering is not the correct option since that would  REMOVE  the data that doesn ' t match the filtering criteria.

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

To add totals to a view using the Analytics pane:

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

Distribution Pane

Explanation

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

Explanation

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

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

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

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

According to the official Tableau documentation:

Depending on the version the extract was created in, Tableau extract files can have either the .hyper or .tde file extension. Extract files are a local copy of a subset or entire data set that you can use to share data with others, when you need to work offline, and improve performance. For more information, see Extract Your Data.

Explanation

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

AND

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.

The LATEST Tableau Desktop Sepcialist exam blueprint now requires you to know some basics about animations as well!

NOTE: Animations are DISABLED by default and must be manually enabled.

You can also reset all settings to default by clickin on ' Reset All '

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

This is 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

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.

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

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

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

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

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

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 card 6  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 field 7

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.

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.

Explanation

Bin are a user-defined grouping of numerical data in the data source.

According to the official Tableau documentation: It ' s sometimes useful to convert a continuous measure (or a numeric dimension) into bins.

Have a look at the following image. When we right click a measure, we get the following options:

However, for a dimension (this is because the  DATA TYPE  of this dimension is a string:

But what if we have a dimension of type  NUMBER (NUMERIC DIMENSION) ? See below:

We can clearly create bins from dimensions too - they just have to be numeric :)

For more information, please refer to :  https://help.tableau.com/current/pro/desktop/en-us/calculations_bins.htm

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

Explanation

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

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

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

The 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

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.

According to the official documentation, the following are the requirements for using relationships:

1) When relating tables, the fields that define the relationships  must  have the same data type. Changing the data type in the Data Source page does not change this requirement. Tableau will still use the data type in the underlying database for queries.

2) You can ' t define relationships based on geographic fields.

3) Circular relationships aren ' t supported in the data model.

4) You can ' t edit relationships in a published data source.

5) You can ' t define relationships between published data sources.

6) Your workbook must use an embedded data source for you to be able to edit relationships and performance options in the Data Source page in Tableau Online or Tableau Server.

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.

When creating an extract in Tableau, there are several options to control how much data is included in the extract. These options include hiding all unused fields to reduce the size of the extract, aggregating the data for visible dimensions to summarize it, and applying filters to extract only the data that meets certain criteria.

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

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/

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 can change the device layout of a dashboard by using the Dashboard pane or the Dashboard menu. The Dashboard pane allows you to select a device type and customize the layout for that device. The Dashboard menu allows you to create a new device layout or copy an existing one.  The Format menu and the Layout pane do not have options for changing the device layout 1

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

Explanation

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.

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

Exporting the visualisation gives us a static view of the visualisation.

It is NOT possible to interact with it, use filters, or dynamically enter anything in a visualisation exported PDF.

In Tableau Desktop, you can save views as PDF files rather than printing them as hard copies. You do not need to have Adobe Acrobat installed on your computer.

When you print an individual sheet to PDF, filters in the view are not included. To show filters, create a dashboard containing the sheet and export the dashboard to PDF. (IMPORTANT)

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

Measure names and values CANNOT be deleted in Tableau like other columns can. These are auto-generated.

Calculated Fields, and Number of records can both be deleted.

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.

Explanation

You can export the data in a Tableau data source, including all or part of the records from your original data. Alternatively, you can export only the portion of data used to generate the view.

Since the question mentions the data used to build the view, we ' ll focus on that :

*Export data in the view to Microsoft Access or .csv*

Export the data that is used to generate the view as an Access database (Windows only) or .csv file (Mac only).

1) In Tableau Desktop, select Worksheet > Export > Data.

2) Select a location and type a name for your Access database or .csv file.

3) Click Save.

4) If you ' re on Windows, the Export Data to Access dialog box displays to give you the option to immediately use the new Access database and continue working in Access without interrupting your work flow.

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To clean and automatically fix the data issues in our data source -  This is the definition of Data Interpreter.

To rename the field in the original data source -  We never modify the original data source when managing metadata. All changes are local to Tableau for our convenience only.

All other options can be modified using the Manage Metadata property.

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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

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:

The following are the official definitions from the Tableau documentation for the various file types:

1) .tds (Tableau Data Source) - To not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you ' ve made on top of the actual data such as changing default properties, creating calculated fields etc. (CORRECT ANSWER)

2) .twbx ( Tableau packaged workbook) - To create a single zip file that contains a workbook along with any supporting local file data and background images. This is great for sharing your work with others who don’t have access to the original data.

3) Extract (.hyper or .tde) – To create a local copy of a subset or entire data set that you can use to share data with others, when you need to work offline, and improve performance.

3) (.twb) Workbooks – To hold one or more worksheets, plus zero or more dashboards and stories.

 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 border 6  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 dimension 7  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 dimension 8  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

For Standard Deviation and Variance, we don ' t need to use quick table calculations, since they are available by default. See below:

However, as seen in the types of quick table calculations available in Tableau, Rank and Moving Average belong to only this category.

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.

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

Graphical user interface, text, application, email, Teams Description automatically generated

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

Graphical user interface Description automatically generated with low confidence

Explanation

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

Follow the steps below:

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.

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 data 5  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 data 4

To invert the color intensity of a quantitative range in Tableau, you should use the " Reversed " option. This option inverts the color scheme so that the colors representing the higher values are swapped with those representing the lower values. For example, if a color scale initially shows dark colors for high values and light colors for low values, using " Reversed " will switch this so that dark colors represent low values and light colors represent high values. This option is particularly useful for better visual distinction and interpretation in certain data scenarios.

Explanation

Yes, it is very much possible to use measures in the same view multiple times. For example, refer to the image below:

We are using  BOTH  the  Sum  of the revenue and the  AVG  of the revenue in the same view!

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 quarter 1  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 date 1  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 source 2

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.

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)

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.

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 card 4  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 data 5  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 stars 6  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 view 7  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 view 8

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

When you use the ' Create Set ' option in Tableau, it creates a dynamic set if the conditions for inclusion in the set are based on a calculation or an aggregation that may change as the data is updated or as filters are applied. Fixed sets are static and do not change with data refreshes, while dynamic sets can update to reflect the current state of the data.

Explanation

Tableau recognises a CSV file as a TEXT file, and therefore it is the correct option.

The following are the steps to import a CSV file:

1) From the data connection screen, click on Text:

2) Choose the appropriate file, and click Open:

3) Finally, Tableau imports the data as shown below:

Data blending simulates a traditional left join. The main difference between the two is when the aggregation is performed. A join combines the data and then aggregates. A blend aggregates and then combines the data.

From the official website: