Question

An "Orders" table has 30 columns, and the report only needs the order total by date. Which transformation should you perform?

Select an answer:

Filter the order amount field to not include blanks, and group by using the date column.

Remove the other columns. Group by using the date column and aggregate the appropriate total field.

Remove the other columns, and sort the date as descending.

Change the order total field data type, and remove the other columns.

2. A number field titled "ProductID" defaults to the SUM aggregate function. Which transformation can you apply so that it defaults to COUNT when used throughout other visuals?

Select an answer:

Change the data type to a fixed decimal point.

Convert the data type to String/Text.

Pivot the data by the ProductID field.

Change the data type to only count.

3.Your boss requests that you create a dashboard that includes a visual for your company's annual sales, with months by top 10 products. Which visualization would not be appropriate?

Select an answer:

bar chart

line chart

column chart

KPI

4.What can be customized to provide more insights into a visual when you hover over items?

Select an answer:

conditional formats

legends

tooltips

title

Answer 1

1. Remove the other columns. Group by using the date column and aggregate the appropriate total field.

2. Change the data type to only count.

3. Key Performance Indicator visualization.

4. The most accurate answer is: tooltips.

1. The appropriate transformation for the "Orders" table, where the report only needs the order total by date, would be to group by using the date column and aggregate the appropriate total field.

2. To change the default aggregate function for the "ProductID" field from SUM to COUNT when used throughout other visuals, you would need to change the data type to only count.

3. The visualization that would not be appropriate for creating a visual of the company's annual sales with months by the top 10 products is the KPI (Key Performance Indicator) visualization.

4. Tooltips are customizable elements that appear when you hover over items in a visual representation, such as a chart or graph. They provide additional information or insights about the specific data point or item you are hovering over. Tooltips can be tailored to display relevant details, enhancing the user's understanding of the visual data.