Your question is SQL and Data Manipulation Assessment. Start with the requirements and the three tables on the right.
Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.
Describe how you would handle a multi-part assessment that includes data manipulation and an ML component, and walk through your approach to the SQL and data preparation steps.
For the SQL portion, prepare one modeling row per candidate using the latest completed assessment attempt and its answer records. Exclude candidates without a completed attempt.
candidate_id, region, assessment_date, assessment_score, sql_accuracy, data_cleaning, missing_answer_count, and outcome_label.candidate_id ascending.| Column | Type | Description |
|---|---|---|
| candidate_idPK | INT | Candidate identifier |
| full_name | VARCHAR(100) | Candidate name |
| region | VARCHAR(50) | Candidate region |
| Column | Type | Description |
|---|---|---|
| attempt_idPK | INT | Assessment attempt identifier |
| candidate_id | INT | Candidate associated with the attempt |
| completed_at | TIMESTAMP | Attempt completion timestamp |
| status | VARCHAR(20) | Assessment status |
| assessment_score | DECIMAL(5,2) | Overall assessment score |
| outcome_label | INT | Supervised learning outcome label |
| Column | Type | Description |
|---|---|---|
| answer_idPK | INT | Answer record identifier |
| attempt_id | INT | Assessment attempt identifier |
| question_code | VARCHAR(40) | Feature question category |
| numeric_value | DECIMAL(5,2) | Normalized numeric answer value |