Text columns rarely arrive in the shape a report needs: names come combined, emails hide the domain, product codes carry a prefix. SQL string functions cut and rebuild those values in place, with SUBSTR and POSITION for slicing, concatenation for joining fields, LIKE for simple pattern matching and regular expressions when the pattern is not simple. These questions cover the parsing and matching problems that come up in interviews and in day-to-day cleanup work.
What you will practice
•Slice values with SUBSTR, LEFT, RIGHT and POSITION to pull a prefix, domain or code out of a field
•Build new labels by concatenating columns with || or CONCAT and handling NULL parts
•Match patterns with LIKE and ILIKE, including the % and _ wildcards and how to escape them
•Use regular expressions to extract or replace substrings that a wildcard cannot describe
•Standardise case and whitespace with UPPER, LOWER and TRIM before joining or grouping on text
