Salesforce Analytics-DA-201 - Salesforce Certified Tableau Data Analyst

The correct order of the three actions is:

Add the date to the Columns shelf. Add the segment and the sales to the Rows shelf.

Aggregate the date to month and year.

From the Analytics pane, drag Forecast to the worksheet.

The first action is to add the date to the Columns shelf and the segment and the sales to the Rows shelf. This will create a line chart that shows the daily sales by segment over time. You can use the Show Me menu to choose a line chart if it is not selected by default.

The second action is to aggregate the date to month and year. This will group the daily sales into monthly sales and show the yearly trend. You can right-click on the date field on the Columns shelf and select Month (January 2017) from the menu. You can also drag Year from the Dimensions pane to the Columns shelf before or after Month.

The third action is to drag Forecast from the Analytics pane to the worksheet. This will add a forecast that predicts future sales by segment based on historical trends. You can customize the forecast by clicking on it and using the options on the Marks card.

The other options are not relevant for this scenario. Adding a trend line would show a linear or nonlinear relationship between two measures, but not a prediction of future values. Creating a calculated field that uses the model quantile function would return a value from a statistical model based on a given quantile, but not a forecast.

There are different ways to create a table calculation that shows sales growth over each year, but one possible answer is:

SUM([Sales])

LOOKUP(SUM([Sales]), -1)

PREVIOUS_VALUE(0)

 To calculate the sales growth over each year, you need to compare the current year’s sales with the previous year’s sales and divide the difference by the previous year’s sales. You can use the SUM, LOOKUP, and PREVIOUS_VALUE functions to achieve this. The SUM function returns the total sales for each year. The LOOKUP function returns the value of an expression in a target row, specified as a relative offset from the current row. The PREVIOUS_VALUE function returns the value of the expression in the previous row, or a specified value if there is no previous row. The formula for the table calculation is:

(SUM([Sales]) - LOOKUP(SUM([Sales]), -1)) / PREVIOUS_VALUE(0)

This formula subtracts the sales of the previous year (LOOKUP(SUM([Sales]), -1)) from the sales of the current year (SUM([Sales])) and divides the result by the sales of the previous year. If there is no previous year, the formula uses 0 as the denominator (PREVIOUS_VALUE(0)) to avoid division by zero errors.

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.

To apply a custom data role to a field, you need to select the data type of the field and then choose the data role from the list of available roles. This will validate the values in the field against the data role and mark any invalid values with a red exclamation mark. To fix the invalid values, you can use the Group Values option and select the Spelling algorithm, which will group values that are close in spelling and replace them with the most frequent value in the group. This will help you standardize the values in the Material field and match them with the Role1 data role. References: The information is based on the following sources:

Use Data Roles to Validate your Data - Tableau

New in Tableau Prep: Automatically identify data quality issues with Data Roles

To filter the table to show the Top 10 NOC based on the number of medals won, you need to do the following steps:

Open the link to Book1 found on the desktop. This will open the Tableau workbook that contains the Disciplines worksheet.

Click on the Disciplines tab at the bottom of the workbook to open the worksheet. You will see a table that shows the NOC, discipline, and medals for each country.

Drag Medals from the Measures pane to the Filters shelf. This will open a dialog box that allows you to filter by different criteria.

Select Top from the dialog box. This will show you options to filter by the top or bottom values of a field.

Enter 10 in the text box next to By field. This will filter by the top 10 values of Medals.

Select NOC from the drop-down list next to By field. This will filter by the top 10 values of NOC based on Medals.

Click OK to apply the filter. You will see that the table now shows only 10 rows, one for each NOC with the highest number of medals.

To filter the table to show the members of the Top10 set and the Bottom10 set, you need to do the following steps:

Open the link to Book1 found on the desktop. This will open the Tableau workbook that contains the Disciplines worksheet.

Click on the Disciplines tab at the bottom of the workbook to open the worksheet. You will see a table that shows the disciplines, sales, and profit for each salesperson.

Click on the drop-down arrow next to Salesperson on the Filters shelf. This will open a menu that allows you to filter by different criteria.

Select Set from the menu. This will show you the sets that are available for the Salesperson field. You will see Top10 and Bottom10 as two sets that have been created based on the sales ranking.

Check the boxes next to Top10 and Bottom10. This will filter the table to show only the members of these two sets. You can also click on All to deselect all other values.

Click OK to apply the filter. You will see that the table now shows 20 rows, 10 for each set.