Which types of data can the JSON Parse tool separate into columns?

The JSON Parse tool in Alteryx is specifically designed to extract structured data from JSON formatted text and convert it into a tabular format. The correct answer includes Float, String, Integer, and Boolean, which reflect the types of data that can be parsed effectively from JSON objects.

Floating-point numbers (Float) can represent decimal values, which are commonly found in JSON files where precision is necessary. String data types encompass any text-based information. Integers are whole numbers often used for counting or indexing in JSON, while Boolean values represent true/false states often used in logical conditions. The JSON Parse tool can interpret these types of data from the hierarchical structure of JSON and transform them into separate columns for analysis.

In contrast, the other options contain combinations of data types that do not necessarily align with the typical structures found within JSON data. For example, one option refers to Enum and DateTime, which may not all be directly separated into columns through the JSON Parse tool due to their specific structures or representations. Understanding the nature of the data types that the JSON Parse tool can handle is essential for effectively extracting and analyzing relevant information from JSON files.