SQL String Functions

Real text data is messy — inconsistent case, stray whitespace, values crammed together that should be separate. This series covers reading, cleaning, combining, and extracting pieces of text.

What & Why

Numbers and dates tend to arrive already well-formed. Text almost never does — names typed in all caps, emails with extra spaces, phone numbers formatted five different ways. This series covers the toolkit for combining text (CONCAT, ||), cleaning it (TRIM, UPPER/LOWER/INITCAP), measuring and slicing it (LENGTH, SUBSTRING, LEFT/RIGHT), finding and replacing pieces (POSITION, REPLACE, SPLIT_PART), and aggregating it across rows (STRING_AGG).

See How It Works

BUSINESS QUESTION

Marketing standardizes lead sources before counting them.

idcampaign_idemailcreated_atqualified_atconverted_atlead_scoresourcecountry
3011ana@example.com2024-01-21 09:10:00+002024-01-22 11:00:00+002024-02-02 10:00:00+0086google_adsUS
3021ben@example.com2024-01-24 12:40:00+00NULLNULL52google_adsCA
3032chloe@example.com2024-02-16 08:30:00+002024-02-18 14:20:00+00NULL74emailGB
3043dev@example.com2024-03-20 17:15:00+002024-03-21 09:00:00+002024-04-04 16:00:00+0091linkedinUS
EXAMPLE QUERY
SELECT
  LOWER(TRIM(source)) AS normalized_source,
  COUNT(*) AS leads
FROM marketing.leads
GROUP BY 1
ORDER BY leads DESC, normalized_source ASC;
RESULT — exact output from the displayed Queryflo rows
normalized_sourceleads
google_ads2
email1
linkedin1

LOWER and TRIM preserve the three actual lead-source groups.

Intermediate business practice

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