Text-to-Columns Tool:

• Splits the date range column into two separate columns using the hyphen (-) as a delimiter.

• This creates two new columns: "start" and "end."

Select Tool:

• Renames the newly created fields from the text split to "start" and "end" for clarity.

Generate Rows Tool:

• Creates rows for each area between the "start" and "end" values.

• This expands the dataset by generating individual rows for each intermediate value within the range.

Select Tool (Cleanup):

• Removes any unwanted or unnecessary fields from the dataset to streamline the data structure.

Join Tool:

• Joins a secondary dataset to the primary dataset based on the newly created "area" field.

• Ensures that the merged data aligns with the corresponding ranges.

Summarize Tool:

• Groups the data by specific fields like region, sales representative, and responder.

• Counts the number of unique Customer IDs within these groups.

Result Output:

• Displays the final output after all transformations and summarizations are complete.

Split Field by Comma:

• Splits a single field into multiple columns using the comma (,) as the delimiter.

• Each part of the original field separated by a comma becomes a new column.

Process Field Values:

• Removes double quotes (") from the values in the dataset.

• Assigns the first resulting field to "POEM."

• Removes single quotes (') from the dataset.

• Parses a field as a date value and assigns the third resulting field to "Poem_Read_Date."

Rename and Cleanup:

• Renames the second resulting field to "Poem_ID."

• Changes the data type of "Poem_ID" to INT16 (a 16-bit integer).

• Removes any unwanted or unnecessary fields from the dataset to ensure a clean and usable data structure.