Free and Premium Salesforce Analytics-DA-201 Dumps Questions Answers

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:

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.

To have each record alternate between grey and white, you should change the row banding size to 1 in the Format Shading pane. This setting will ensure that each row has a different shading from the one above and below it, creating an alternating pattern of grey and white rows. References: The answer can be verified through practical application within Tableau or by consulting Tableau’s official learning resources, such as  Tableau Help: Format Shading  or  Tableau Training Pass: Formatting .

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:

Tableau Desktop controls the presentation of printed worksheets through File > Page Setup. The Page Setup dialog contains print-specific settings that are independent of whether the worksheet title is currently visible in the interactive workbook. Under the General settings, Tableau provides a Show section where the analyst can choose whether printed output includes the worksheet title, view, captions, and legends. Therefore, if a hidden title unexpectedly appears in PDF output, the analyst should open Page Setup and disable the title for printing. Export As PowerPoint creates a different output format and does not configure PDF print elements. Share and Export As Version likewise do not control printed worksheet titles. Tableau’s current printing documentation identifies Page Setup as the location for showing or hiding worksheet titles in printed output.

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:

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.

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.

The object that you should add to the dashboard to allow users to switch to a different dashboard in the workbook is Navigation.

Navigation objects are used to create links between dashboards or sheets in a workbook. You can add a navigation object to a dashboard by dragging it from the list of objects and dropping it on the dashboard. You can then configure the navigation object to specify the destination dashboard or sheet that you want users to navigate to when they click on it.

You can learn more about navigation objects and how to use them in this article:

To combine two sets, they must have at least one dimension in common. In this case, Customers of 2020 and Top N Customers both have Customer Name as a dimension, so they can be combined using set operations such as union, intersection, or difference. Sellers of 2020 and Top N Products have different dimensions (Seller Name and Product Name), so they cannot be combined. References:

In Tableau, sets can be combined if they are created from the same dimension. From the options provided, " Customers of 2020 " and " Top N Customers " are likely created from the same dimension (Customers). Therefore, these two sets can be combined to create a new set that includes or excludes members based on the combined criteria. Combining sets like " Top N Products " with " Customers of 2020 " would not be feasible unless they are from the same dimension, which is typically not the case.

A Top N filter is applied to categorical members, so the field being filtered should be a discrete dimension. When a discrete dimension is placed on the Filters shelf in Tableau Desktop, the Filter dialog provides General, Wildcard, Condition, and Top tabs. The Top tab can then retain the top or bottom N members based on an aggregate measure, such as the top 10 customers by SUM(Sales). A continuous measure uses quantitative range filtering rather than the dimension-member Top interface. A table calculation is evaluated later in Tableau’s order of operations and is not the field type used to configure a standard Top N dimension filter. A set can itself be defined using a Top rule, but it is a separate object rather than the required field type for this filter. Therefore, C is correct.

To schedule a refresh of the data, you need to ensure that Tableau Server or Tableau Online can access the database without prompting for credentials. This can be done by embedding the credentials in the workbook or the published data source. You also need to extract the data from the database and publish it as a separate data source or as part of the workbook. A live connection would not allow you to refresh the data on a sched ule, as it would always query the database directly. A hyper file is a format for storing extracted data, but it is not a requirement for scheduling a refresh. References:

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

Tableau Help: Embedding Database Credentials

Tableau Help: Extract Your Data

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 filter regions based on the highest sales and allow users to specify the number of regions shown, you should perform these actions in order:

Answer area:

Create an integer data type parameter named Param1.

Drag Region to the Filters shelf.

Configure a Top filter by field. Use Param1 and filter by the sum of Sales.

 To create a dynamic filter that lets users choose the number of regions to display, you need to use a parameter and a top filter. A parameter is a user-defined variable that can be used in calculations, filters, and reference lines. A top filter is a type of filter that shows only the top or bottom N values based on a specified field or expression.

In this question, you want to filter regions based on the highest sales. You also want users to be able to specify the number of regions shown. To achieve this, you need to follow these steps:

First, you need to create an integer data type parameter named Param1. This parameter will allow users to enter a number that will determine how many regions to show. You can create a parameter by right-clicking on the Data pane and selecting Create Parameter. Then, you need to specify the name, data type, current value, and allowable values for the parameter. In this case, you can choose Integer as the data type, 10 as the current value, and All as the allowable values. You also need to show the parameter control by right-clicking on the parameter and selecting Show Parameter Control. This will display a slider or a text box where users can enter or adjust the parameter value.

Next, you need to drag Region to the Filters shelf. This will open the Filter dialog box, where you can choose how to filter the Region field. You can filter by general, wildcard, condition, or top. In this case, you want to filter by top, so you need to select the Top tab.

Finally, you need to configure a top filter by field. Use Param1 and filter by the sum of Sales. This will filter the Region field by showing only the top N regions based on the sum of Sales, where N is the value of the parameter Param1. You can configure a top filter by field by selecting By field in the Top tab, then choosing the parameter Param1 from the drop-down list, and selecting the aggregation function Sum and the field Sales from the other drop-down lists. This will create a filter expression that looks like this: Top Param1 by SUM(Sales).

By following these steps, you will create a filter that shows only the regions with the highest sales, and allows users to change the number of regions shown by adjusting the parameter value.

To complete the formula, you should drag the option MAX from the list of options and drop it into the first blank space, and then drag the option [Sales] and drop it into the second blank space. The formula will look like this: Option (MAX) Option ([Sales] ). This formula will calculate the maximum value of the sales field for each country. You can use this formula to create a calculated field that will show the highest sales amount for each country in your data source. References:

Create a Simple Calculated Field - Tableau

MAX Function - Tableau

Tableau Certified Data Analyst Study Guide

To create an image of the chart that you can add to the annual report, you can use either the Export option or the Copy option from the Worksheet menu. The Export option will allow you to save the image as a file in a specified location, name, and format. The Copy option will allow you to copy the image to the clipboard and paste it into another application, such as Microsoft Word. Both options will let you choose which elements to include in the image, such as title, caption, legend, etc. References:

Export Views from Tableau Desktop to Another Application

Copy and Paste Views from Tableau Desktop to Another Application

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

For a published Tableau data source, the Connect capability controls whether a user can connect to that data source from Tableau Desktop and use it for analysis. Tableau permissions also determine whether the content is visible within the site and project hierarchy, but among the choices, Connect is the capability specifically associated with making a usable published data source available for connection. Certification does not restrict the list to certified sources only, and ownership is not required; users can connect to data sources created by other publishers when permissions allow it. A user’s home directory is not the governing scope for published Tableau data sources. Therefore, the correct choice is the data sources for which the user has the required Connect permission, subject to normal site and content visibility permissions.

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:

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.

Sales:  B. Columns

Profit:  D. Rows

Customer Name:  C. Detail on the Marks card

Category:  A. Color on the Marks card

To create the visualization, you need to drag Sales to Columns, Profit to Rows, Customer Name to Detail on the Marks card, and Category to Color on the Marks card. This will create a scatter plot that shows the relationship between Sales and Profit for each Customer Name, with different colors for each Category.

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:

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.

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 determine the Rank Score value for Student ID 4220, we look at the visualization provided and apply the table calculation of RANK(AVG([Score])) . This function will rank the average scores in ascending order by default, with the lowest score receiving the rank of 1.

Based on the provided visualization, the scores for the students are as follows (from lowest to highest average score):

Student ID 4183: 39 (Rank 1)

Student ID 4220: 71 (Rank 6)

Student ID 4247: 71 (Rank 6, same score as ID 4220 so they share the same rank)

Student ID 4124: 75.5

Student ID 4050: 64

Student ID 4205: 67

Student ID 4056: 66

Since Student ID 4220 has an average score of 71, which is the third-highest score, it shares the rank with Student ID 4247. However, since Tableau ranks without gaps, the actual rank assigned is 6, considering that there are two students with a rank of 4 (due to the same average score being the second lowest), making the next rank number 6.

Note: The actual ranks for the highest scores are not provided, but they are not needed to determine the rank for Student ID 4220.

To create the dashboard as shown in the image, you need to use a vertical layout container that will adjust the height of the sheets according to the window size. You also need to set the Fit to Entire view option for both sheets so that they will resize proportionally when you click a category on the top sheet. This way, you can achieve the desired effect of having the bottom sheet expand to fill the space left by the top sheet when it filters out some categories. References:

Size and Lay Out Your Dashboard - Tableau

Create a Dashboard - Tableau

Format Dashboard Layout in Tableau - GeeksforGeeks

The matching-pattern capability is configured in an Input step in Tableau Prep Builder. When connecting to file-based data such as text files or Excel files, Tableau Prep can include multiple files and create an input union by using wildcard or matching-pattern criteria. This allows similarly named files to be combined into a single table as they are brought into the flow. A separate Union step combines already-added tables or inputs, but the question specifically asks where a single table can be created from a matching pattern of multiple file names. Join combines tables based on key fields, while New Rows generates missing sequential records. Because wildcard file matching is part of the file-ingestion configuration, Input is the correct step.

A full outer join preserves every row from both physical tables, returning matched records where possible and null values where a corresponding row does not exist. That directly satisfies the requirement to retain books that appear in only one of the two incomplete tables. A Tableau relationship can also satisfy the requirement because relationships keep logical tables separate and defer physical joining until analysis time. Tableau dynamically determines the appropriate joins based on fields used in the visualization and makes the row and column data from related tables potentially available without permanently collapsing the tables. Left or right joins would discard unmatched rows from one side, while an inner join retains only matches. Therefore, Full outer join or Relationship model is the correct combination.

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.

1) Open Tableau prep

2) Create a new column ...

3) Union the sales ...

4) Join the sales ...

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

A suspended data-driven alert can be managed from the My Content area in Tableau’s web interface. Tableau’s current documentation states that when an alert has failed enough times to become suspended, an alert owner can locate the suspended alert in My Content and choose Resume Alert. Tableau now also supports resuming an alert directly from the notification email or from the Alerts panel of the affected view, but neither of those choices appears in this question. Shared with Me manages content shared by other users; Tableau Prep’s notification area does not administer Tableau Server or Cloud data alerts; and Tableau Desktop’s Data Source page is unrelated to server-side alert scheduling. Therefore, among the supplied answers, C remains valid.

To refresh an extract on Tableau Server, you need to select the workbook, select Refresh Extracts, and then add a new extract refresh. You can specify the frequency and time of the refresh, as well as any custom options. You can have multiple extract refreshes for the same workbook with different schedules. References:

On Tableau Server, you can manage the scheduling of extract refreshes by selecting the specific workbook and configuring additional refresh schedules as needed. This allows for multiple refresh triggers, such as the regular Monday at 10:00 AM schedule, as well as an additional trigger for the last day of the month at 18:00.

The two formulas that will return a value of true if a month has sales greater than $50,000, otherwise the formula must return a value of false, are:

B. IIF(SUM([Sales]) > 50000, TRUE, FALSE) D. [Sales] > 50000

The IIF function is a logical function that returns one value if a condition is true, and another value if the condition is false. In this case, the condition is SUM([Sales]) > 50000, which means that the sum of sales for a month is greater than $50,000. The function will return TRUE if the condition is true, and FALSE if the condition is false.

The comparison operator > is a logical operator that returns TRUE if the left operand is greater than the right operand, and FALSE otherwise. In this case, the operands are [Sales] and 50000, which means that the sales for a month are greater than $50,000. The operator will return TRUE if the sales are greater than $50,000, and FALSE otherwise.

The other options are not correct for this scenario. The IN function is a logical function that returns TRUE if a value is in a set of values, and FALSE otherwise. In this case, the value is SUM([Sales]), which is not in the set of values (50000). The function will always return FALSE. The MAX function is an aggregation function that returns the maximum value in a field or expression. In this case, the field or expression is [Sales] , 50000, which is not valid syntax. The function will return an error. References:

Tableau Desktop supports custom mark shapes by loading image files from the Shapes folder inside My Tableau Repository. The analyst should copy the new shape files into a folder under My Tableau Repository\Shapes. Tableau uses that folder as a custom shape palette, and the analyst can then select the shapes from the Marks card by choosing Shape and editing the shape assignment. Once custom shapes are used, they are stored with the workbook, which supports sharing the visualization with other users. Dragging image files directly into a workbook does not register them as reusable mark shapes, and a URL cannot be used as the workbook’s shape repository. My Tableau Prep Repository is also incorrect because Tableau Prep is not where Tableau Desktop mark-shape palettes are stored.

Both the ZN and IFNULL functions in Tableau can be used to replace NULL values with zeros. The ZN function converts NULL to zero directly, while the IFNULL function allows you to specify that NULL should be replaced with zero. Both will result in showing zero for any NULL values in the Profits field.

Tableau provides various options to export data from a worksheet. The formats available are typically those that are best suited for visualization or further data analysis. The options include:

.png for exporting images of the visualizations

.xlsx for exporting data in a format that can be opened with Microsoft Excel

.pptx for creating PowerPoint presentations with the visualization embedded

These formats are designed to facilitate sharing and presenting the insights derived from Tableau visualizations, or for conducting further analysis in tools like Excel.

The required logic must first evaluate the activity history independently for each Call ID, which is why a FIXED LOD expression is appropriate. {FIXED [Call ID] : ...} establishes Call ID as the calculation grain regardless of the visualization’s dimensions. Within each call, [Activity Name] = " Assign Technician " produces a Boolean condition. Applying MAX to that condition determines whether an assignment activity exists for that call. If one exists, the calculation returns 0; otherwise it returns 1. The outer SUM then totals the calls that never received an assignment. INCLUDE does not provide the required fixed call-level evaluation, while the other expressions either count activity records rather than calls or do not form valid LOD logic for the requirement. Therefore, A is correct.

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.

RANK is a table calculation, and Tableau evaluates ordinary dimension filters before table calculations. Filtering out Phones , which is the highest-sales Technology sub-category, removes that mark before Tableau recalculates Rank for the remaining Technology members. Machines therefore moves from Rank 2 to Rank 1, Accessories from Rank 3 to Rank 2, and Copiers from Rank 4 to Rank 3. The Furniture members—Chairs, Tables, Bookcases, and Furnishings—remain in their existing partition and therefore retain their current ranks. Phones itself disappears rather than receiving a new displayed rank. Tableau documents RANK as ranking values within a partition and confirms through its order of operations that dimension filtering takes place before table calculations are evaluated. Therefore, Machines, Copiers, and Accessories are the three affected sub-categories.