Lakehouse vs Warehouse Decision Guide
Seven questions for choosing between a Fabric Lakehouse and a Warehouse based on who writes the data, who reads it and how it is operated.
Implementing Analytics Solutions Using Microsoft Fabric
Fabric Analytics Engineer
A practical DP-600 guide for analytics engineers working with Fabric data preparation, semantic models, security, and lifecycle management.
Last verified against Microsoft Learn:
Core skill areas
- Prepare and query data for analytics
- Secure and maintain Fabric analytics assets
- Design, build, and optimize semantic models
Practical experience recommended
- Building or maintaining a Fabric lakehouse or warehouse
- Creating dimensional models and working with SQL and DAX
- Managing deployment, security, refresh, and performance concerns
Overview
DP-600 is the exam behind the Microsoft Certified: Fabric Analytics Engineer Associate credential. It fits people who design and manage analytical assets in Fabric, especially warehouses, lakehouses, and semantic models. Treat it as a structured validation of platform knowledge—not proof that someone can make every production tradeoff.
Who it is for
- Analytics engineers building governed, reusable data products in Fabric
- BI professionals moving into enterprise-scale semantic modeling
- Data engineers who own the analytical serving layer
- Practitioners who already use SQL and want to formalize Fabric, DAX, KQL, and lifecycle knowledge
What you should know
Be comfortable choosing data stores, shaping dimensional data, querying with SQL, KQL, and DAX, and reasoning about access control, deployment, refresh, and performance. Hands-on familiarity with both data preparation and semantic models makes the study guide much more concrete.
Skills covered
The current official blueprint groups the work into preparing data, maintaining an analytics solution, and implementing and managing semantic models. Always re-check the official study guide before scheduling because Microsoft updates the measured skills.
How I would prepare
- Read the current official skills measured and mark each item strong, partial, or new.
- Complete the Microsoft Learn material only for genuine gaps first.
- Build a small lakehouse or warehouse with a star schema and a semantic model.
- Add security, source control, deployment, refresh, and performance checks.
- Explain why you chose each storage and modeling option.
- Use the free practice assessment, then revisit weak domains.
Practical projects to build
- A Bronze-to-Gold analytics flow with a dimensional serving layer
- A semantic model that compares storage modes and documents the tradeoffs
- A governed workspace deployment with Git, access controls, and a repeatable release path
- A reporting solution that measures refresh and query performance
Study resources
Start with the official study guide and Microsoft Learn modules. Use Javi on Data articles and the certification study planner to turn each domain into a build, troubleshooting exercise, or architecture decision.
Exam-day preparation
Revisit the official exam page, test the exam sandbox, confirm identification and technical requirements, and avoid last-minute memorization. Focus on reading scenario constraints carefully and choosing the option that best fits them.
After passing
Write down what the credential validated, then keep a project or case study that demonstrates how you apply it. Share the architecture, tradeoffs, and operational lessons—not only the badge.
Renewal
Microsoft role-based certifications generally renew annually through a free online Microsoft Learn assessment during the eligibility window. Check your Microsoft Learn profile and the official renewal page for the policy and your exact dates.