Stitch Data -

SELECT * FROM crm_table c JOIN transactions t ON c.user_id = t.user_id (OR logic) If one key fails, use another.

CREATE TABLE id_mapping AS SELECT anonymous_id, user_id, MIN(first_seen_at) AS first_seen FROM events WHERE user_id IS NOT NULL GROUP BY anonymous_id, user_id; stitch data

SELECT * FROM table_a a LEFT JOIN table_b b ON a.email = b.email OR a.phone = b.phone ⚠️ Be careful with OR – it can cause record multiplication. For complex cases (anonymous + logged-in users), build a mapping table. SELECT * FROM crm_table c JOIN transactions t ON c

df_crm['email'] = df_crm['email'].str.lower().str.strip() df_support['email'] = df_support['email'].str.lower().str.strip() A. Simple Join (Deterministic) Use when you have a perfect matching key. df_crm['email'] = df_crm['email']

Stitching data refers to the process of combining or joining multiple datasets from different sources into a single, unified dataset. The goal is to create a complete view by linking records that belong to the same entity (e.g., customer, product, transaction) across systems.