In a customer database, you may have first names and last names in separate columns. To create a full name column for better readability or for use in a mail merge, you would need to combine these two columns.

If you have a list of users' names and the domain of their email address, you can combine these two pieces of information to create a complete email address.

In inventory management, product codes may be split across multiple columns (e.g., category code, item code). To create a full product code, you would need to combine these columns.

Addresses are often stored in multiple columns (street, city, state, zip). To create a full address field for printing labels or for use in a mapping service, you would need to combine these columns.

In data analysis, you may need to create a unique identifier for each row by combining data from multiple columns. This can be useful for joining tables or for tracking data over time.

In digital marketing, you might have a base URL in one column and the specific page path in another. To generate the complete URL for each page, you would need to combine these two columns.

In a dataset, dates and times might be in separate columns. To analyze or visualize the data on a timeline, you would need to combine the date and time fields into a single datetime field.

In a report, you may need to combine text from multiple columns into a single cell to create a specific format or to include all necessary information in one place.