Which method transforms unique values in a column into new column headers?

The correct method that transforms unique values in a column into new column headers is the Cross Tab functionality in Alteryx. This tool is specifically designed to pivot data, turning unique values from a specified column into headers for new columns. For example, if you have a dataset that lists sales by product and region, using Cross Tab can convert the regions into separate columns, allowing for a more organized view of the data where each region's sales appear under the corresponding header.

When utilizing the Cross Tab tool, you specify which field's unique values will become the new headers and which field will provide the values that populate the new headers. This capability is particularly useful for summarizing data and enhancing readability, facilitating analysis across different categories or dimensions.

In contrast, the other options serve different purposes: Transpose rearranges rows and columns but does not create new headers; Append Fields combines data from two datasets side by side based on a common field but does not pivot or change structure; Union stacks datasets vertically but does not create new column headers based on unique values. Understanding these distinctions is essential to effectively applying the right tools in Alteryx for data transformation tasks.