You have a database notebook that is running slow. What steps would you take to optimize it?

Start by examining the SQL queries executed in the notebook. Use the database’s EXPLAIN or EXPLAIN ANALYZE to see the query plan and identify full table scans, missing indexes, or expensive joins. Add or adjust indexes on columns used in WHERE, JOIN, and ORDER BY clauses. If the notebook runs the same query repeatedly, consider materialized views or caching the result set. Normalize or denormalize data as appropriate to reduce join complexity. Partition large tables by a high‑cardinality column to limit scanned data. Use proper data types and avoid implicit casts. Enable query caching if the database supports it. Profile the notebook’s execution time per cell and look for bottlenecks such as slow network calls or large data transfers. Optimize the notebook code by batching queries, using parameterized statements, and minimizing round‑trips. Finally, ensure the database configuration (memory, buffer pool, parallelism) matches the workload, and monitor resource usage to detect contention. These steps help reduce latency and improve overall notebook performance.