Databricks Bootcamp — Lesson 1: Foundations, Architecture, and Use Cases

Topics Covered

• Data platform architecture and workload selection
• Ingestion patterns for batch and streaming data
• Storage, lakehouse, warehouse, and table design
• Transformation, orchestration, and data quality
• Roles, prerequisites, terminology, and success criteria
• Business and technical requirement mapping
• Solution boundaries, dependencies, and assumptions

Practical Activity

Analyze a representative use case, document requirements, and create a solution or platform map.

• Document assumptions, selected features or services, and expected outcomes.
• Record validation evidence, risks, dependencies, and corrective actions.
• Summarize the decision in a reusable implementation or operations note.

Lesson Outcome

Learners can explain and apply the lesson topics within a realistic Azure Data scenario.