CompTIA Data+ (DA0-002)Data MiningMedium
A data analyst is preparing a dataset of customer feedback where survey responses include a free-text field for 'Suggestions'. Many entries contain leading or trailing spaces, multiple spaces between words, or unwanted newline characters. To clean this text for consistent analysis, which combination of SQL string functions would be most effective?
- ACONCAT and SUBSTRING
- BLENGTH and LEFT
- CTRIM and REPLACE
- DUPPER and LOWER
Show answer & explanationAnswer & explanation
Correct answer: C. TRIM and REPLACE
TRIM is effective for removing leading and trailing spaces. REPLACE is crucial for handling multiple spaces between words (by replacing ' ' with ' ') and for removing unwanted newline characters (by replacing specific newline characters with an empty string or a single space). Combined, they address the described text cleansing needs.
Why the other options are wrong
- A. CONCAT combines strings; SUBSTRING extracts parts. Neither directly addresses excess spaces or newlines.
- B. LENGTH returns string length; LEFT extracts characters from the left. These are not suitable for cleaning spaces or newlines.
- D. UPPER and LOWER change case, not remove spaces or newlines.
SQL String Cleansing
The process of using SQL string functions to clean and standardize text data by removing unwanted characters, spaces, or inconsistencies.
- Common tasks include removing leading/trailing spaces, extra internal spaces, special characters, and converting case.
- Functions like TRIM, LTRIM, RTRIM, REPLACE, and sometimes regular expressions are frequently used.
- Ensures text data is consistent and ready for analysis or storage.
Memory trick: Cleaning text with SQL: TRIM the ends, REPLACE the messy middle.