Data Visualization and Analytics Flashcards

An analyst has built a dashboard with a map showing sales by state and a bar chart showing sales by product category. They want to enable users to click on a state on the map to filter the bar chart to show data for only that selected state. Which of the following should the analyst configure?

Answer: A Filter Action

A Filter Action is the correct choice because it is designed to use the data from a selection in one sheet (the source sheet, in this case, the map) to filter the data in another sheet (the target sheet, the bar chart). This creates an interactive experience where users can dynamically explore relationships in the data.

You are creating a waterfall chart to visualize how different product sub-categories contribute to the total profit. After creating a running total of profit, what is the next essential step to transform the standard bars into the floating blocks characteristic of a waterfall chart?

Answer: Change the mark type to Gantt Bar.

The key to a waterfall chart in Tableau is using the Gantt Bar mark type. After calculating a running total, the Gantt Bar allows you to control the start and end point of each mark. You then use a separate field (typically the negative of the measure) on the Size shelf to control the length of each bar, creating the floating effect.

A financial analyst wants to compare the distribution of sales values for four different regions. They are particularly interested in identifying the median, interquartile range, and any potential outliers for each region side-by-side. Which chart type is most suitable for this analysis?

Answer: Box and Whisker Plot

A Box and Whisker Plot is specifically designed to show the distribution of a dataset through a five-number summary: minimum, first quartile, median, third quartile, and maximum. This makes it ideal for comparing distributions across different categories (like regions) and easily identifying key statistical measures like the median and interquartile range, as well as spotting outliers.

Which of the following describes a primary functional difference between a Tableau Group and a Set?

Answer: Groups are static and manually defined, while Sets can be dynamic based on conditions.

The most significant difference is that Groups are always static; members are manually selected and do not change unless edited. Sets, however, can be dynamic. A dynamic set's members can automatically update based on a defined condition, such as 'Top 10 Customers by Sales', which will change as the underlying data refreshes.

An analyst is building a view to show the Top 10 customers by sales for each year. They place [Customer Name] on Rows, `SUM(Sales)` on Columns, and filter [Customer Name] to the 'Top 10 by SUM(Sales)'. They then add a dimension filter for `YEAR([Order Date])`. They notice that for some years, fewer than 10 customers are displayed. Why is this happening?

Answer: The dimension filter on year is being applied after the Top N filter is calculated.

According to Tableau's Order of Operations, Top N filters are computed before dimension filters. Tableau first identifies the overall Top 10 customers across all years in the dataset. Then, it applies the dimension filter for a specific year. If some of those overall top 10 customers had no sales in the selected year, they are filtered out of the view, resulting in fewer than 10 customers being shown. To fix this, the year filter should be added to context.

When using Tableau's built-in forecasting feature, which of the following is a key requirement for the view?

Answer: The view must contain at least one measure and one date dimension.

To enable forecasting in Tableau, the view must contain at least one measure (the value you want to forecast) and at least one date dimension (to provide the time series). While a dimension with integer values can sometimes be used instead of a date, the presence of a date dimension is the primary requirement.