1. What is the key difference between being data-informed and data-driven?
2. What makes a metric actionable in a metrics tree?
3. What is the purpose of a power analysis in A/B testing?
4. Why should you avoid drawing early conclusions during an A/B test?
5. What is the purpose of understanding table granularity?
6. How can you determine a table's primary key?
7. What is the purpose of root-cause analysis (RCA)?
8. What is a key step when defining hypotheses during RCA?
9. Why is joining tables important in data analysis?
10. What is the use of the HAVING clause in SQL?
