Analytics-DA-201 Questions and Answers

A Running Total accumulates the measure sequentially across the addressing dimension. With Year on Columns and SUM(Downloads) in the view, Tableau starts with the first year ' s downloads and progressively adds each subsequent year ' s value to the accumulated total. The resulting bars therefore represent all downloads received up to each year since release rather than the downloads for that individual year alone. YTD Total is intended for accumulation within a calendar year and commonly restarts with the new year. Percent of Total expresses each value as a proportion of the full partition, while Year Over Year Growth compares the relative change between consecutive annual values. Tableau lists Running Total as a standard quick table calculation specifically for cumulative analysis. Therefore, B is the appropriate calculation.

The target visualization shows a subtotal after the members of each Category while retaining the individual Sub-Category rows. In Tableau, Analysis > Totals > Add All Subtotals inserts subtotal rows or columns when multiple dimensions are present on Rows or Columns. Here, Category and Sub-Category are both on Rows, so Tableau can calculate a subtotal for each Category group. Show Column Grand Totals and Show Row Grand Totals create totals for the entire view along the corresponding direction; they do not insert a separate total inside every Category section. Column Totals to Top only changes the placement of existing column totals. Because the requirement is to add a Total row for Furniture, Office Supplies, and Technology individually, Add All Subtotals is the correct command.

To make a workbook available in Tableau Online, you need to publish it from Tableau Desktop to Tableau Online. You can do this by selecting Publish Workbook from the Server menu, signing in to your Tableau Online account, choosing a project and a name for your workbook, and clicking Publish. This will upload your workbook and its data sources to Tableau Online, where you can view, edit, and share it with others. References:

Tableau Certified Data Analyst Exam Prep Guide , page 10, section “Publishing and Scheduling Data Refreshes”

Tableau Help: Publish a Workbook

The same person can appear multiple times because an individual may have won several awards. Consequently, COUNT([Name]) would count award records rather than distinct people and would overstate the number of award recipients. COUNTD([Name] ) returns the number of distinct non-null names, so each person is counted only once regardless of how many award rows are associated with that person. Tableau’s aggregate-function documentation defines COUNTD as returning the number of distinct items in a group and demonstrates its use when unique entities must be counted. MAX([Name]) returns a single maximum string value according to the applicable sort sequence. ATTR tests whether a group contains one unique value, while COVAR is a statistical covariance function requiring quantitative expressions. Therefore, C correctly counts unique award-winning people.

A data source filter is a filter that applies to all the worksheets that use the same data source. It filters the data before any other filters or calculations are applied. You can add a data source filter from the Data Source page by clicking on the Add button next to Filters.

The type of filter that will appear in the Edit Data Source Filters dialog box is a dimension filter on all the sheets. This means that you can choose a dimension from your data source and filter it by values, range, condition, or top/bottom. The filter will affect all the worksheets that use that dimension.

The other types of filters are not data source filters and will not appear in the Edit Data Source Filters dialog box. A table calculation filter is a filter that applies to a table calculation, such as percent of total or running total. A top N condition filter is a filter that shows only the top or bottom N values of a measure or dimension based on a condition. A context filter is a filter that creates a subset of data that other filters can use.

The Item hierarchy separates the top-level floating objects from the objects nested under the Tiled section. In the exhibit, Show/Hide, Filters Container, and Legend appear at the top level before the Tiled branch. Total Sales and Horizontal Container are nested inside vertical containers under Tiled, so they belong to the tiled layout structure. Tableau distinguishes tiled items, which participate in a non-overlapping layout grid, from floating items, which can be positioned and layered independently. In Tableau Desktop, floating objects appear at the top level of the Item hierarchy and can be reordered to control their layering. Reading the hierarchy therefore identifies B, D, and E as floating, while A and C are contained within the tiled hierarchy and are not floating objects.

To combine the tables and meet the requirements, you should use a left join. A left join will keep all the records from the left table (Employeelnfo) and match them with the records from the right table (DepartmentInfo) based on the common field (Department ID). If there is no matching record in the right table, the fields from the right table will be null. This way, you will retain all the records from Employeelnfo, and also include the Department Name, Size, and VP fields from DepartmentInfo. Every record will have a full name because it is a field from the left table. A left join will look like this:

An INCLUDE LOD expression is specifically useful when a calculation must incorporate a finer-grained dimension that is not already present in the visualization. INCLUDE adds the specified dimension to the level of detail established by the dimensions currently in the view, calculates the expression at that finer grain, and then allows Tableau to reaggregate the result at the view’s level. For example, { INCLUDE [Customer Name] : SUM([Sales] ) } can calculate sales per customer even when Customer Name itself is absent from the displayed view. If the dimension is already present in the view, INCLUDE generally adds no additional granularity for that field. The dimension does not specifically need to reside on the Marks card, Rows/Columns shelves, or Filters shelf. Therefore, Not in the View is the correct answer.

The requirement is based on total sales by store, so the filter must operate on the Store Number dimension while evaluating an aggregated Sales condition. Tableau dimension filters provide a Condition tab that can retain dimension members according to an aggregate measure, for example SUM([Sales]) > = 500. Applying that logic as an extract filter ensures that only qualifying store members are included in the resulting extract. Filtering the Sales measure by an “at least” row-level value would incorrectly evaluate individual records rather than each store’s total. A Top filter ranks members and is intended for top or bottom N selection, not for a fixed minimum total. Therefore, the analyst should filter Store Number by a condition based on Sales, which corresponds to option B.

To add two sheets to the dashboard that support the Show/Hide button, you can add them to either a horizontal or a vertical container. A container is an object that can hold one or more sheets or other objects and allow you to arrange them in a layout. A Show/Hide button is a feature that lets you hide or show a container and its contents on the dashboard. You can add a Show/Hide button to any container, whether it is tiled or floating, by using the drop-down menu of the container and selecting “Add Show/Hide Button.” You can also customize the appearance and behavior of the button.

To add a horizontal or a vertical container to the dashboard, you can drag them from the Objects pane to the dashboard. A horizontal container will arrange the sheets or objects horizontally, while a vertical container will arrange them vertically. You can then drag the sheets you want to add from the Sheets pane to the container. You can resize and reorder the sheets or objects within the container by using the handles and arrows.

The other objects in the Answer Area, such as text, image, web page, blank, navigation, download, and extension, do not support the Show/Hide button. They are either static elements that cannot hold other objects, or dynamic elements that require user interaction or external sources. You can add them to the dashboard as well, but they will not have the same functionality as a container with a Show/Hide button.

A reference line is used in Tableau to display a line at a constant value or a computed value such as an average, median, minimum, or maximum in a bar chart. In this case, adding a reference line would allow you to show the median, upper quartile, and lower quartile, which corresponds to the changes shown in the bar chart.

To build the scatter plot shown in the image, you need to place the Profit measure on the Rows shelf and the Sales measure on the Columns shelf. This will create a Cartesian chart with Profit as the y-axis and Sales as the x-axis. Then, you need to change the mark type to Circle on the Marks card. This will display the data points as circles that vary in size according to the Quantity measure. You can also add color or shape encoding to the marks to show additional dimensions or measures in the view. References:

Build a Scatter Plot

Understanding and Using Scatter Plots

Scatter plot in Tableau

To unsubscribe from the views, you should use the My Content area of Tableau web pages. This area allows you to manage your subscriptions, as well as your workbooks, views, and data sources. You can select the views you want to unsubscribe from, click Actions, and then click Unsubscribe. You can also change the subscription options, such as the schedule, the format, or the message. References:

Create a Subscription to a View or Workbook - Tableau

Tableau Certified Data Analyst Study Guide

To create a new calculated dimension field named Category that meets the given conditions, you can use either the IF or the CASE logical function. Both functions allow you to evaluate an expression and return a value based on different scenarios. Option A uses the IF function with multiple ELSEIF clauses to check the value of the Subject field and assign it to either ‘Sciences’ or ‘Humanities’. Option D uses the CASE function with multiple WHEN clauses to do the same thing. Both options will produce the same result, but the CASE function is more concise and easier to read. Option B is incorrect because it will assign ‘Humanities’ to any subject that contains ‘Science’ in its name, which is not the desired outcome. Option C is incorrect because it will only check if the subject ends with ‘Computer Science’ and ignore the other subjects. References:

Logical Functions - Tableau

Tableau Certified Data Analyst Study Guide

To configure the shapes to be much larger than the line, you need to duplicate Population and drag it to the second Marks card. This will create a dual axis chart with two measures on one axis. You can then select Shape on one Marks card and Line on another Marks card, and adjust the size of each mark independently using the Size slider or menu. References: https://help.tableau.com/current/pro/desktop/en-us/multiplemeasures_dualaxes.htm https://help.tableau.com/current/pro/desktop/en-us/marks_markproperties_size.htm

In a dual-axis chart in Tableau, if you want to have two different visual mark types (like a shape and a line) and configure them differently (such as making one larger than the other), you would need to duplicate the measure. You then drag this duplicate to the second Marks card (which represents the second axis). There, you can adjust the size of the marks (shapes, in this case) independently of the line marks on the first Marks card.

Extensions in Tableau are web-based programs that can interact with dashboards. To add a button that allows users to export the dashboard as an image, you would use an Extension object. This could be a custom extension designed to trigger the download of the dashboard view as an image.

we need to create a calculated field that displays the count of returns only for the first year in the table. To do this, we can use the following formula:

IF FIRST () = 0 THEN COUNT (Returns) END

This formula uses the FIRST () function, which returns the number of rows from the current row to the first row in the partition. If the current row is the first row, then FIRST () returns 0. The IF statement checks if this condition is true, and if so, it returns the count of returns for that row. Otherwise, it returns NULL.

To complete the formula in the calculated field, you should select the following options from the drop-down menus:

FIRST ()

0

COUNT (Returns)

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

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

This formula uses a parameter (Pick Measure) to switch between the Sales and Profit measures. When the user selects ' 1 ' , it shows Sales, and when ' 2 ' is selected, it shows Profit. This dynamic switching is enabled by the Case function.

In Tableau, the RANK function assigns a rank to each row within a partition of the data, based on the value of the field being ranked. It is important to understand that the rank is recalculated whenever the underlying data or the partitioning changes.

In the given scenario, the Overall Rank is based on the Sales figures, while the Rank (presumably) is based on the Sales within the Category. When filtering on the condition where [Overall Rank] - 1, it means we are excluding the sub-category that has an Overall Rank of 2.

Looking at the data:

Furnishings has an Overall Rank of 8, which does not meet the filter condition ([Overall Rank] - 1). Therefore, its rank remains the same.

Tables have an Overall Rank of 3. When the sub-category with an Overall Rank of 2 is removed (Chairs in this case), Tables move up in the overall ranking. However, since Tables are the top-ranked within the Furniture category, their Rank within the category would remain unchanged at 1.

Chairs have an Overall Rank of 2, which meets the filter condition and thus will be removed from the view. We cannot determine the change in Rank for Chairs because they are filtered out.

Accessories have an Overall Rank of 5. If any sub-category with a higher Overall Rank (1 to 4) is removed, the rank of Accessories within the Technology category could change because it is currently ranked 3 in its category. With the removal of Phones (Overall Rank 1), the Rank of Accessories could potentially increase.

Copiers have an Overall Rank of 6, which does not meet the filter condition. Therefore, its rank remains the same.

Machines have an Overall Rank of 4. If we remove Phones (Overall Rank 1), Machines will move up in the overall ranking and potentially within the Technology category as well, changing its Rank from 2 to 1.

Phones have an Overall Rank of 1, which does not meet the filter condition of being Overall Rank 2. Therefore, its rank remains the same.

Bookcases have an Overall Rank of 7, which does not meet the filter condition. Therefore, its rank remains the same.

Based on this analysis, when the sub-category with an Overall Rank of 2 (Chairs) is removed, the Rank value will change for Tables, Accessories, and Machines, as they will move up in the overall ranking within their respective categories. However, it ' s important to note that while Tables will move up in the overall ranking, their rank within the Furniture category would not change as they are already at the top. The rank changes for Accessories and Machines are due to the removal of Phones, which is ranked higher overall and within the Technology category.

The formula in option B calculates the percent difference in sales relative to the same quarter the previous year. It subtracts the sales of the same quarter from the previous year from the current year’s sales, and then divides this by the previous year’s sales. This gives a percentage change, which aligns with what is shown in the Calculation field of your dataset. The LOOKUP function returns the value of a specified offset from the current row in the partition. In this case, the offset is -4, which means the value of the same measure four rows above the current row. This corresponds to the same quarter of the previous year, assuming the data is sorted by quarter. References:

LOOKUP Function - Tableau

Table Calculations - Tableau

Tableau Certified Data Analyst Study Guide

Published data sources are shown according to the user’s access within the Tableau site, not simply because the sources exist somewhere on the server. Tableau permissions govern whether a user can discover and connect to published data sources, and the Connect capability is specifically required for ordinary users to work with a published source. Site boundaries also matter: Tableau Server can host multiple sites, and content from another site is not automatically exposed to a signed-in user. Therefore, the best choice is that the list contains the data sources the analyst has access to within the current site. Options that describe every source on the whole Tableau Server are too broad, while restricting results to a particular project state is not the general rule.

To make Sales appear automatically as shown in the second table, you should change the default number format of the Sales field. The default number format is how Tableau displays a field when you drag it to a worksheet. You can change the default number format by right-clicking on the field and selecting Default Properties > Number Format from the menu. This will open a dialog box where you can choose a category, such as Currency or Percentage, and customize the options, such as decimal places or prefixes.

In this case, you want to change the default number format of Sales to Currency with zero decimal places and a custom prefix of “S”. This will make Sales appear as “S” followed by the rounded value in thousands.

The other options are not correct for this scenario. Changing the data type of Sales to String will not affect how it appears on a worksheet. Creating a calculated field that uses a formula will not change the default number format of Sales, but create a new field that you have to drag to a worksheet. Converting Sales to Attribute will return only one value for each partition of data, which will not show any variation over time. References: https://help.tableau.com/current/pro/desktop/en-us/formatting.htm https://help.tableau.com/current/pro/desktop/en-us/formatting_change_default.htm

To achieve the formatting as shown in the example, where sales figures are displayed with a " K " to represent thousands and rounded to the nearest thousand (e.g., $20K, $44K, etc.), you would need to adjust the default number format of the Sales field in Tableau. By changing the default number format, every instance where the Sales field is used would automatically reflect this new formatting. This is more efficient than creating a calculated field as it preserves the numeric nature of the field, allowing for further numerical operations and aggregations.

https://kb.tableau.com/articles/howto/filtering-data-with-a-parameter?lang=fr-fr

After creating a parameter named Choose Region, you want to use it to filter the chart based on the user ' s selection. To do this, you would create a calculated field with the formula [Region] = [Choose Region] and add this calculated field to the Filters card. This will dynamically filter the chart to display data only for the region that matches the user’s selection in the Choose Region parameter.

1) Open Tableau prep

2) Create a new column ...

3) Union the sales ...

4) Join the sales ...

To configure the dashboard action, you should select Filter as the action type, Select as the run action on option, and All Fields as the target filters option. This will ensure that when a user selects a city on the map, the bar chart will show only the data for the selected city based on all fields in common between the two worksheets. The action will run only when the user selects a different city. References: https://help.tableau.com/current/pro/desktop/en-us/actions.htm https://help.tableau.com/current/pro/desktop/en-us/actions_filter.htm

Tableau ' s Layer Control is specifically designed for maps containing multiple geographic mark layers. When enabled, it gives users an interactive panel from which individual map layers can be shown or hidden and interactions with particular layers can also be enabled or disabled. Tableau Desktop authors enable this feature through Map > Map Options > Layer Control before publishing the workbook. A parameter could theoretically drive custom calculations, but it is unnecessary because Tableau already supplies native layer-visibility controls. The Filter shelf filters underlying data values rather than directly controlling geographic mark-layer visibility. A dual-axis map is also unnecessary and is more limited than Tableau ' s current multi-layer mapping architecture. Therefore, C is the direct, officially supported method for allowing users to toggle map layers independently.

To minimize the whitespace between the sheets, you should configure the padding of the sheets and the dashboard. Padding is the amount of space between the edge of a sheet or dashboard and its content. You can adjust the padding by using the Layout tab in the Format pane. You can reduce the padding for each sheet by selecting the sheet and changing the values for the inner and outer padding. You can also reduce the padding for the dashboard by selecting the dashboard and changing the values for the outer padding. Reducing the padding will make the sheets and the dashboard more compact and eliminate unnecessary whitespace. References:

Format Dashboards - Tableau

Tableau Certified Data Analyst Study Guide

In Tableau, to replace a sheet on a dashboard, you can simply drag the desired sheet (Sheet2 in this case) from the sheets list onto the dashboard where the current sheet (Sheet3) is. This will replace the existing visualization with the new one.

Parameter actions allow a user to change a parameter value by directly interacting with marks in a visualization, such as by selecting or hovering over a mark. When that parameter is referenced by a calculated field, changing the parameter immediately changes the calculation ' s result and therefore the information displayed in the visualization. This enables highly interactive experiences without requiring the user to manipulate a separate parameter control. Tableau also supports parameter actions with reference lines, filters, and SQL queries. The action does not literally convert a parameter into a filter, nor does it create a static view or restrict interaction to predefined filters. Therefore, D best represents the advantage tested here: selections in the visualization can dynamically update parameter-driven calculations and consequently change the displayed analysis.

To combine the tables by using Tableau Prep and include only values from Table1 that do not match any values in Table2, you should use a left only join. A left only join is a type of join that returns only the rows from the primary table (Table1) that have no matching rows in the secondary table (Table2). The field values from Table2 will appear as null values in the combined table. A left only join is also known as an anti-join or an exclusion join. References:

Tableau Certified Data Analyst Exam Prep Guide , page 9, section “Preparing Data”

Tableau Help: Join Your Data

Tableau Help: Left Only Join

To organize the tables in the Data pane based on the type of data contained within the tables, you should use folders. Folders are a way to manually group fields, parameters, sets, or tables in the Data pane according to your preference. You can create folders by right-clicking on the fields or tables you want to group and selecting Folders > Create Folder. You can also drag and drop fields or tables into existing folders. You can name the folders according to the type of data they contain, such as sales, customer, product, etc. Folders can help you find and access the fields or tables you need more easily and efficiently. References:

Organize and Customize Fields in the Data Pane - Tableau

Tableau Certified Data Analyst Study Guide

To configure the dashboard to ensure that selecting a data point on the map only filters the Detail table, you should select Ignore Actions from the context menu of Sales over time. Ignore Actions is a feature that allows you to exclude a sheet from being affected by any actions on the dashboard, such as filters or highlights. You can select Ignore Actions by right-clicking on a sheet on the dashboard and selecting Ignore Actions from the menu.

In this case, you want to exclude Sales over time from being filtered by the map, so you should select Ignore Actions from its context menu. This will make Sales over time ignore any selections on the map and show all values. The Detail table will still be filtered by the map as usual.

The other options are not correct for this scenario. Removing Dashboard Item will delete Sales over time from the dashboard, which is not what you want. Deselecting Use as Filter will disable the map as a filter for any sheet on the dashboard, which is not what you want. Selecting Deselect will clear any selections on the map, but it will not prevent Sales over time from being filtered by future selections. References: https://help.tableau.com/current/pro/desktop/en-us/actions.htm https://help.tableau.com/current/pro/desktop/en-us/actions_ignore.htm

On a Tableau dashboard, when a map is used as a filter, it affects all other sheets in the dashboard by default. To restrict the filter action to only affect the Detail table and not the ' Sales over time ' chart, you would modify the action settings. By selecting " Ignore Actions " from the context menu of the ' Sales over time ' chart, it will no longer respond to the filtering action initiated by selecting data points on the map.

To connect a Tableau workbook to a dataset in a Microsoft Excel spreadsheet, you need to select New Data Source from the Data menu. This will open the Connect pane, where you can choose Microsoft Excel as your data source and browse for your spreadsheet file. You can then drag and drop your sheets or tables to join or union them in the data source page. References: https://help.tableau.com/current/pro/desktop/en-us/connect_basic.htm https://help.tableau.com/current/pro/desktop/en-us/connect_excel.htm

When connecting to a dataset in Tableau Desktop, you would go to the ' Data ' menu and select ' New Data Source ' . This allows you to connect to various types of data sources, including Microsoft Excel spreadsheets, where you can then select the specific file you wish to connect to.

When you sign in to a Tableau Server site from Tableau Desktop and search for a published data source, you will see all the data sources published to the site within the folders to which you have access. You will not see data sources published to other sites or folders that you do not have permission to view. You can also filter your search by project, owner, or tag. References: https://help.tableau.com/current/pro/desktop/en-us/connect_basic.htm https://help.tableau.com/current/pro/desktop/en-us/connect_tableauserver.htm

When signed in to Tableau Server from Tableau Desktop, you ' ll only be able to see the data sources that have been published to the site and are within the folders that you have been granted access to. Tableau ' s permission and project structure mean that you won ' t see all data sources from the entire server unless you have permissions to do so.

The LAST() function in Tableau returns the number of rows from the current row to the last row in the partition. When you compute using ' Order Date ' , it will change the partitioning of the calculation. If ' Consumer ' in ' 2018 ' is the last row in its partition when computed by ' Order Date ' , then LAST() will return 0 for that cell.

The LAST() function in Tableau is a table calculation that returns the number of rows from the current row to the last row in the partition. The value of LAST() is 0 for the last row, increases by 1 for each row above the last row, and can be negative for rows below the current row if there are such rows in the partition.

In the provided visualization, LAST() is set to compute using Table (across). Changing the compute mode to use " Order Date " will adjust the partitioning of the data upon which the LAST() function is calculated. Since " Order Date " is likely to be a unique value per row (assuming each order has a unique date), each row becomes its own partition.

For the Consumer segment of the year 2018, if " Order Date " is unique for each row, then the last row in each partition (in this case, each individual row) will have a LAST() value of 0 because there are no other rows in the partition - it ' s the last row of its own partition.

Therefore, when you change the compute mode of LAST() to use " Order Date " , each cell under the Consumer segment for the year 2018 will have the LAST() value of 0, because each order date creates a partition of one, making every row the last in its partition.

Data interpreter is a feature that helps you clean and structure your data in Excel before importing it into Tableau. It detects and removes any headers, footers, subtotals, or other elements that are not part of the actual data. It also splits any merged cells and fills in any missing values. In this case, data interpreter provides the following results:

It removes the first three rows and the last two rows that contain headers and footers.

It splits the merged cells in column A and fills in the missing values with “Fiction” or “Non-Fiction”.

It does not remove or change any other rows or cells.

Therefore, the number of rows of data that will be ingested into Tableau as values is 17, which is the number of rows left after removing the headers and footers. References: https://help.tableau.com/current/pro/desktop/en-us/importing_cleaning_up_data.htm https://help.tableau.com/current/pro/desktop/en-us/importing_data_interpreter.htm

Based on the Data Interpreter ' s results and the provided Excel dataset screenshot, the number of rows of data that will be ingested into Tableau as values is 17. The Data Interpreter has identified and excluded headers and footers, and the rows with actual data are considered for analysis.

Publishing the Excel-based goals data as its own managed data source provides the most appropriate architecture for a file that must be updated regularly and reused alongside an existing published revenue source. The analyst can publish the Excel connection as an extract and configure the appropriate refresh mechanism, after which the dashboard workbook connects to both centrally governed published sources. Tableau documents that published extract data sources can be refreshed on a schedule and that every connected workbook then benefits from the refreshed data. Merely embedding an Excel extract in one workbook would couple refresh management to that workbook, while simply uploading a flat file through web authoring does not guarantee updates to the original changing file. Modifying the ERP system is unnecessary. Therefore, option D provides the intended reusable and maintainable Tableau design.

Based on the line chart provided, each point on the line chart represents the average sales for a given month, and the percentage values indicate the change in average sales compared to the previous month. The month of November shows a significant increase from the month of October, indicated by a large upward spike on the chart and a high percentage increase.

To combine the two tables that contain data about books in a library and ensure that all the data is retained, you should use a full outer join. A full outer join is a type of join that returns all rows from both tables, regardless of whether there is a match or not. If there is no match, null values are filled in for the missing fields.

To perform a full outer join, you need to do the following steps:

Connect to both tables as your data sources in Tableau. You can use either live or extract connections.

Drag one table to the canvas and drop it on top of another table. This will create a join between them based on a common field.

Click on the join icon between the tables and select Full Outer Join from the drop-down list. This will change the join type to full outer join and show all rows from both tables.

Optionally, you can add or remove join clauses by clicking on Add or Remove buttons next to each clause. You can also change or rename fields by clicking on them.

The other types of joins are not correct for this scenario. An inner join returns only the rows that have a match in both tables, which will exclude any books that are missing from either table. A left join returns all rows from the left table and only the matching rows from the right table, which will exclude any books that are only in the right table. A right join returns all rows from the right table and only the matching rows from the left table, which will exclude any books that are only in the left table. References: https://help.tableau.com/current/pro/desktop/en-us/joining_tables.htm https://help.tableau.com/current/pro/desktop/en-us/join_types.htm

When combining two datasets that are both incomplete and where it ' s important to retain all data from both sources, a full outer join is appropriate. This type of join ensures that all records from both tables are included in the combined dataset, even if there are no matching records in the other table.