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| rowid | event_id | name | clean_description | location_room | start_date_clean | start_time | end_time | pre_reg_flag | paid_flag | laptop_flag | speakers_cleaned | session_type | keywords | skill_level | session_title |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 218 | 4270 | SQL CARwash: Cleaning dirty data | Spend enough time around databases and inevitably you’ll come across one that has an obnoxious number of variations on city names: New York City. New York. NYC. NY. And yes, even NY City. If you’re not sure how to handle that, this session is for you. We’ll cover how to deal with multiple spellings and misspellings, strange date formats and category codes, as well as a few other tricks and tips for using SQL to clean data. This session will be most useful if: You are familiar with basic SQL statements. | 15 | 2019-03-09 | 2019-03-09 11:30:00 | 2019-03-09 12:30:00 | 0 | 0 | 0 | Madi Alexander, Bloomberg BNA | 3 | 2 | SQL CARwash: Cleaning dirty data |