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DBT can be used on Oracle to perform an approximate relation match by using its fuzzy string matching capabilities. Fuzzy matching is a technique that allows the comparison of two strings that are similar but not exactly the same.

There are various DBT functions that can be used for fuzzy matching, including soundex, levenshtein, and jaro-winkler. These functions can be combined with SQL queries to identify approximate matches between two tables based on a set of predefined criteria, such as similarity score, edit distance or fuzzy match percentage.

To perform an approximate relation match, follow these steps:

1. Identify the two tables that need to be matched
2. Define the criteria for matching, for example, column names or a set of similar values.
3. Use DBT SQL queries to perform a fuzzy match of the columns between the two tables.
4. Review the results of the fuzzy match, and identify potential matches based on the similarity score or other criteria.
5. Optionally, apply filtering, sorting or grouping to further refine the results.

Overall, DBT can help to automate the process of approximate matching, and can be a powerful tool for data quality and integration tasks in Oracle databases.