Cost & Performance Optimization — Databricks Certified Data Engineer Professional

The official DATABRICKS documentation our Cost & Performance Optimization practice questions are cited to. Review the primary sources, then practise.

Official references for this objective

Databricks — Cost Management for Serverless Compute: Notebooks, Jobs, and Pipelines | Databricks

entitlements that grant or revoke serverless access per user, group, or service principal, and per-workload rate limits that cap the spend rate of an individual
Databricks — Diagnosing Performance Bottlenecks in Databricks Lakehouse | Databricks

how to distinguish query-level inefficiencies from data layout issues, concurrency pressure, and system-level constraints, and how to interpret execution plans and runtime signals to identify
Databricks — Forecasting at Databricks: One Framework Behind Consumption and Infra Cost | Databricks

Unified Forecasting Framework, the backend behind AI_Forecast() function scheduled on Lakeflow Jobs validates model selection across the hierarchies
Databricks — Optimize Lakehouse Cost and Performance With Intelligent Storage and Liquid Clustering | Databricks

including Automatic Liquid Clustering on Unity Catalog managed tables, adaptive layouts that handle evolving query patterns, and metadata-driven optimizations that reduce unnecessary data scans
Databricks — Optimizing AI/BI Dashboard Performance: Best Practices for Speed and Scale | Databricks

Design datasets and queries for fast, interactive dashboard performance - Leverage caching, query optimization, and warehouse configuration effectively - Use automatic materialization for the right