Data Science, Analytics, Databricks, Data Cleaning.
email by using the following query: CREATE OR REPLACE TEMP VIEW users_clean3 AS select *, regexp_extract(email, "(?<=@).+", 0) AS email_domain from users_clean2 Conclusion: We have just demonstrated how we can use databricks notebooks to clean data using SQL. We went through 4 steps to remove null