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.

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.

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.

Common Characters: Find and group values that have letters or numbers in common. This option uses the ngram fingerprint algorithm that indexes words by their unique characters after removing punctuation, duplicates, and whitespace. This algorithm works for any supported language. This option isn ' t available for data roles. For example, this algorithm would match names that are represented as " John Smith " and " Smith, John " because they both generate the key " hijmnost " . Since this algorithm doesn ' t consider pronunciation, the value " Tom Jhinois " would have the same key " hijmnost " and would also be included in the group.

There are different ways to prepare the data in Tableau Prep, but one possible answer is:

Answer area:

Join the tables.

Aggregate the data by Sales Team.

Add the following filter to the Employees table: Sale Team - Team Alpha.

 To analyze sales trends over time for every sales team, you need to combine the data from the Orders and Employees tables. You can do this by joining the tables on the Rep ID column, which is a common identifier for both tables. This will create a single table with all the columns from both tables. Next, you need to aggregate the data by Sales Team, which is the level of analysis you want. You can do this by grouping the data by the Sales Team column and applying an aggregation function (such as sum, average, count, etc.) to the other columns that you want to measure (such as Total Amount, Rep Tenure, etc.). This will create a summary table with one row for each sales team and the aggregated values for the other columns. Finally, you need to filter the data to focus on a specific sales team, such as Team Alpha. You can do this by adding a filter to the Employees table and selecting only the rows where Sales Team equals Team Alpha. This will remove the rows for other sales teams and keep only the data for Team Alpha.

To show the corresponding region when users hover their mouse over any of the bars, you need to drag Region to Tooltip on the Marks card. This will add Region as a field in the tooltip text that appears when users hover over a mark. You can also customize the tooltip text by editing it in the Tooltip dialog box. References: https://help.tableau.com/current/pro/desktop/en-us/buildmanual_shelves.htm https://help.tableau.com/current/pro/desktop/en-us/formatting_tooltips.htm

To show additional information such as the corresponding region when hovering over a bar in Tableau, you can drag the ' Region ' field to the ' Tooltip ' shelf on the ' Marks ' card. This will ensure that when a user hovers over a bar representing a city, the tooltip will dynamically display the region associated with that city.

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 area where the current sheet (Sheet3) resides. This action will replace the existing sheet with the new one. Right-clicking and adding to the dashboard adds an additional sheet rather than replacing, and the context menu options mentioned in the other choices are not the standard methods for replacing sheets within a dashboard.