The Microsoft Certified: Fabric Data Engineer Associate (DP-700) replaced the retired DP-203 in March 2025. It is a 100-minute, ~40–60 question exam focused entirely on Microsoft Fabric — lakehouses, dataflows, pipelines, real-time intelligence, and security. It costs $165 USD, requires a 700/1000 to pass, and must be renewed annually via a free online assessment.
- Understand what changed from DP-203 to DP-700 and why it matters
- Evaluate whether the Fabric Data Engineer certification fits your career
- Break down the three exam domains and their weight distribution
- Follow a structured 4–6 week study plan with official Microsoft resources
- Compare DP-700 vs AWS DEA-C01 vs Databricks DE Associate
Quick Answers
What happened to the DP-203 Azure Data Engineer certification?
Microsoft retired DP-203 and the Azure Data Engineer Associate credential on March 31, 2025. The replacement is DP-700, which leads to the Microsoft Certified: Fabric Data Engineer Associate credential. DP-700 is built entirely around Microsoft Fabric instead of Azure Synapse and Data Factory.
How hard is the DP-700 exam?
Moderate difficulty. The exam assumes expertise in data loading patterns, data architectures, and orchestration within Microsoft Fabric. Candidates comfortable with SQL, PySpark, and KQL who have hands-on Fabric experience can prepare in 4–6 weeks. Those new to Fabric may need 8–10 weeks.
What is the passing score for DP-700?
700 out of 1,000 on a scaled scoring model. The exam has approximately 40–60 questions (Microsoft does not publish an exact count) and you have 100 minutes of exam time.
How long is the Fabric Data Engineer certification valid?
Microsoft associate certifications must be renewed annually. Renewal is free — you pass an online assessment on Microsoft Learn before the expiration date. No need to retake the full exam.
Microsoft's data engineering certification went through a major shift in 2025. The DP-203 (Azure Data Engineer Associate), which tested Azure Synapse, Data Factory, and Azure SQL, was retired on March 31, 2025. Its replacement — DP-700 — is built entirely around Microsoft Fabric, the unified analytics platform that consolidates data engineering, data science, real-time analytics, and business intelligence into a single SaaS product.
If you held DP-203 or are considering your first Microsoft data engineering credential, DP-700 is the exam to take. This guide covers the exam format, what's on it, how to study, and whether it's worth your time.
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Learn how Careery can help youWhat Is the Microsoft Fabric Data Engineer Associate (DP-700)?
- Microsoft Certified: Fabric Data Engineer Associate (DP-700)
A Microsoft intermediate-level certification that validates a candidate's ability to implement data engineering solutions using Microsoft Fabric — including data ingestion, transformation, lakehouse and warehouse implementation, real-time intelligence, security, and monitoring.
The certification tests three equally weighted skill areas:
- Implement and manage an analytics solution (30–35%) — workspace configuration, lifecycle management, security, governance, and orchestration
- Ingest and transform data (30–35%) — batch and streaming data loading patterns, transformations using SQL, PySpark, KQL, and Power Query
- Monitor and optimize an analytics solution (30–35%) — monitoring pipelines, resolving errors, and optimizing lakehouse, warehouse, and streaming performance
DP-700 is the only current Microsoft certification for data engineers. It is entirely focused on Microsoft Fabric — if your target jobs use Fabric, OneLake, or the Fabric lakehouse stack, this is the credential to get.
DP-203 Is Retired: What Changed and Why
The retirement of DP-203 reflects Microsoft's strategic pivot from individual Azure services (Synapse Analytics, Data Factory, Azure SQL) to the unified Microsoft Fabric platform. Here is what changed:
The DP-203 credential and all renewal assessments expired on March 31, 2025. If you held DP-203, it no longer appears as an active certification. You need to pass DP-700 to earn the current Fabric Data Engineer Associate credential — there is no automatic upgrade or transition path.
DP-700 is not a minor update to DP-203 — it is a fundamentally different exam on a different platform. Former DP-203 holders need to study Microsoft Fabric specifically, not just refresh their Azure knowledge.
Is the DP-700 Certification Worth It in 2026?
When It Helps Most
- Engineers at Microsoft Fabric shops: Many enterprise organizations are migrating from Azure Synapse to Fabric. A DP-700 credential signals that you've made the transition.
- Consultants in the Microsoft ecosystem: Partners and consulting firms that deliver Microsoft solutions often require or strongly prefer certified engineers. Some Microsoft partner tiers require a minimum number of certified employees.
- Career changers targeting enterprise data roles: Large enterprises in finance, healthcare, and government skew heavily toward Microsoft tooling. DP-700 gives you credibility in that market segment.
- Former DP-203 holders: If you already understood Azure data services, the jump to Fabric is manageable. Recertifying keeps your credential current.
When It May Not Be the Priority
- Teams using AWS or GCP exclusively: If your target companies are all-in on AWS or Google Cloud, an AWS DEA-C01 or Google Cloud Professional Data Engineer credential is more directly applicable.
- Senior engineers deep in Fabric already: If you've been building production Fabric solutions for a year, your track record speaks louder than a cert. Consider investing that time in a complementary cert like Databricks instead.
For the full picture of how certification affects data engineer pay — including experience-level breakdowns and location adjustments — see our Data Engineer Salary Guide.
DP-700 has the highest ROI for engineers working in the Microsoft ecosystem, especially those transitioning from legacy Azure Synapse to Fabric. If your target job market is AWS-dominant, start with AWS DEA-C01 instead.
Exam Overview: Format, Scoring, and Prerequisites
Key Differences from AWS Exams
Unlike AWS certifications (which are valid for 3 years), Microsoft associate certifications expire annually. The good news: renewal is free. You take an unproctored online assessment on Microsoft Learn before the expiration date. It takes 30–60 minutes and tests updated content.
Prerequisites
Microsoft does not require a prerequisite exam. However, the expected background includes:
- Subject matter expertise in data loading patterns and data architectures
- Experience with SQL, PySpark, and KQL (Kusto Query Language)
- Hands-on experience with Microsoft Fabric workspaces, lakehouses, data warehouses, and real-time intelligence
If you're coming from a DP-203 background or another cloud, KQL (Kusto Query Language) is likely the biggest new skill to learn. It's used for real-time analytics in Fabric's Real-Time Intelligence workload. Allocate extra study time here.
100 minutes, ~40–60 questions, 700 to pass. Annual renewal (free). No prerequisites, but expect to need SQL, PySpark, and KQL proficiency.
What's on the Exam: Domain Deep-Dive
DP-700 has three equally weighted domains, each covering 30–35% of the exam. This even distribution means you cannot afford to skip any domain.
Domain 1: Implement and Manage an Analytics Solution (30–35%)
- Workspace configuration: Spark settings, domain settings, OneLake settings, data workflow settings
- Lifecycle management: Version control, database projects, deployment pipelines
- Security and governance: Workspace-level and item-level access controls, row-level / column-level / object-level security, dynamic data masking, sensitivity labels, OneLake security, workspace logging
- Orchestration: Choosing between Dataflow Gen2, pipelines, and notebooks. Designing schedules and event-based triggers. Implementing orchestration patterns with parameters and dynamic expressions.
Security and governance questions in this domain are the most nuanced. Know the difference between workspace-level, item-level, and row/column-level access controls — the exam tests when to use which.
Domain 2: Ingest and Transform Data (30–35%)
- Loading patterns: Full and incremental loads, dimensional model preparation, streaming data loading
- Batch data: Choosing data stores, choosing between dataflows / notebooks / KQL / T-SQL for transformation, shortcuts, mirroring, pipeline ingestion, transformations in Power Query (M), PySpark, SQL, and KQL
- Streaming data: Choosing streaming engines, native vs. mirrored vs. shortcut storage in Real-Time Intelligence, accelerated vs. non-accelerated shortcuts, eventstreams, Spark structured streaming, KQL processing, windowing functions
The streaming data section is where DP-700 diverges most from DP-203. Know eventstreams, Real-Time Intelligence storage options, and KQL windowing functions. This sub-domain surprises many candidates who focused only on batch processing.
Domain 3: Monitor and Optimize an Analytics Solution (30–35%)
- Monitoring: Data ingestion, data transformation, semantic model refresh, alerts
- Error resolution: Pipeline errors, dataflow errors, notebook errors, eventhouse errors, eventstream errors, T-SQL errors, shortcut errors
- Performance optimization: Lakehouse table optimization, pipeline optimization, data warehouse optimization, eventstream/eventhouse optimization, Spark performance tuning, query performance tuning
All three domains are equally weighted (30–35% each). You cannot afford to skip any one domain. The streaming and real-time intelligence content in Domain 2 is the most likely blind spot for candidates coming from a batch-processing background.
How to Study: 4–6 Week Plan
This plan assumes you have some experience with Microsoft data tools (Azure SQL, Data Factory, or Synapse). Candidates completely new to the Microsoft ecosystem should add 2–4 weeks.
Week 1: Orientation and Gap Analysis
Goal: Understand the exam scope and identify what you don't know.
- Read the DP-700 study guide end-to-end. Map each skill statement to concepts you know vs. don't know.
- Take the free practice assessment on Microsoft Learn to establish a baseline.
- If you're new to KQL, start the KQL learning path immediately — it takes the longest to internalize.
- Sign up for a Microsoft Fabric free trial if you don't already have access.
Weeks 2–3: Core Learning Paths
Goal: Work through the official training content with hands-on practice.
Complete the five official Microsoft Learn paths that map directly to the exam:
- Ingest data with Microsoft Fabric (~5 hours)
- Implement a Lakehouse with Microsoft Fabric (~7 hours)
- Implement Real-Time Intelligence with Microsoft Fabric (~5.5 hours)
- Implement a data warehouse with Microsoft Fabric (~6 hours)
- Manage a Microsoft Fabric environment (~3.5 hours)
Each path includes hands-on exercises. Don't skip them — the exam includes scenario-based questions that require practical familiarity.
Weeks 4–5: Practice Exams and Weak Area Review
Goal: Simulate exam conditions and close gaps.
- Retake the Microsoft Learn practice assessment. Compare to your Week 1 baseline.
- Try the exam sandbox to experience the interactive question types before the real exam.
- For every wrong answer, go back to the relevant Microsoft Learn module. Focus on why the correct answer is correct.
- Create flashcards for common decision points: "When to use Dataflow Gen2 vs. a notebook vs. a pipeline" and "When to use a lakehouse vs. a warehouse."
Week 6: Final Review and Exam
Goal: Consolidate and take the exam.
- Review the study guide's skill statements one final time. Can you explain each bullet point?
- Schedule the exam at least 1 week in advance.
- Focus last-minute review on KQL syntax and Real-Time Intelligence storage options — these are the most commonly missed topics.
I'm preparing for the Microsoft Fabric Data Engineer Associate (DP-700) exam. My background: - Current role: [YOUR ROLE] - Experience with Microsoft data tools: [LIST TOOLS — e.g., Azure SQL, Data Factory, Synapse, Power BI] - Experience with Microsoft Fabric specifically: [NONE / BASIC / INTERMEDIATE] - Familiarity with KQL: [NONE / BASIC / COMFORTABLE] - Hours per week I can study: [X] - Target exam date: [DATE] Based on the DP-700 exam domains: - Implement and manage an analytics solution (30–35%) - Ingest and transform data (30–35%) - Monitor and optimize an analytics solution (30–35%) Create a week-by-week study schedule that: 1. Prioritizes my weakest areas (especially if KQL is new to me) 2. Includes the specific Microsoft Learn paths for each domain 3. Schedules hands-on lab time in a Fabric trial workspace 4. Reserves the final week for practice assessments only
The official Microsoft Learn paths total ~27 hours of content. Combined with practice assessments and hands-on exploration, 4–6 weeks at 8–10 hours per week is sufficient for most candidates with some Microsoft experience.
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Common Study Mistakes
- Studying DP-203 material for a DP-700 exam — the platforms are fundamentally different (Synapse vs. Fabric)
- Skipping KQL because you're comfortable with SQL — Real-Time Intelligence questions require KQL fluency
- Not using a Fabric trial workspace — the exam tests practical decision-making, not theoretical knowledge
- Treating all three domains as equal time investments — focus extra time on your weakest domain
- Using third-party brain dumps — Microsoft updates exam questions frequently, and dumps often contain outdated or wrong answers
How to Register and Schedule the Exam
Create a Microsoft Learn Profile
Go to learn.microsoft.com and sign in with a personal Microsoft account (MSA). Microsoft strongly recommends using a personal account, not a work/school account — if you leave your organization, exam records tied to a work account are lost and unrecoverable.
Go to the Certification Page
Navigate to the Fabric Data Engineer Associate certification page. Scroll down to Take the exam and click Schedule exam.
Schedule Through Pearson VUE
You'll be redirected to Pearson VUE. Choose between:
- Test center — select a location near you and pick a date/time
- Online proctored — requires webcam, microphone, and a clean desk. Run the Pearson VUE system check before booking.
Prepare Your ID
Bring a government-issued photo ID (passport, driver's license) that matches the name on your Microsoft Learn profile exactly. For online proctored exams, close all background applications and ensure stable internet.
- Certification page: learn.microsoft.com/credentials/certifications/fabric-data-engineer-associate
- Schedule exam (Pearson VUE): Schedule DP-700
- Exam sandbox (practice UI): Exam sandbox demo
- Exam policies: learn.microsoft.com/credentials/support/exam-duration-exam-experience
- Request accommodations: learn.microsoft.com/credentials/certifications/accommodations
DP-700 vs AWS DEA-C01 vs Databricks — Which Should You Get?
Which One First?
- If your target companies use Microsoft Fabric or are migrating from Synapse: DP-700 is the clear choice. Enterprise organizations in finance, healthcare, and government disproportionately rely on Microsoft tooling.
- If job postings mostly mention AWS services (Glue, Redshift, S3): Start with AWS DEA-C01. AWS leads the cloud market in data engineering job postings.
- If you use Databricks daily: The Databricks DE Associate validates Spark and Delta Lake skills. It pairs well with either cloud cert since Databricks runs on AWS, Azure, and GCP. See our Databricks Data Engineer Certification Guide for the full study plan.
- Best two-cert combo for Microsoft shops: DP-700 + Databricks DE Associate. Many Fabric environments also use Azure Databricks for heavy Spark workloads.
Considering AWS instead? See our complete guide to the AWS Data Engineer certification: AWS Data Engineer Certification (DEA-C01): Complete Guide.
For the full breakdown of all data engineering certifications — including Google Cloud Professional Data Engineer and dbt — see our Best Data Engineering Certifications guide.
DP-700 is the right choice for the Microsoft ecosystem. AWS DEA-C01 has broader market reach. If your career is in a Microsoft-heavy industry (finance, healthcare, government), DP-700 gives the strongest signal.
How to Add This Certification to Your Resume and LinkedIn
Resume
- Certifications section: List as "Microsoft Certified: Fabric Data Engineer Associate (DP-700)" with the year earned.
- Technical Skills: Include "Microsoft Fabric" as a platform alongside your cloud skills.
- ATS keywords: Include "DP-700," "Microsoft Fabric," and "Fabric Data Engineer" — recruiters search for all three.
- Certifications feature: Go to Profile → Add section → Licenses & Certifications. Use the official name: "Microsoft Certified: Fabric Data Engineer Associate." Link to your Credly badge.
- Headline update: Example: "Data Engineer | Microsoft Fabric (DP-700) | SQL, PySpark, Power BI."
- Credly badge: Microsoft issues a digital badge via Credly. Share it directly from Credly to LinkedIn for a verified credential that recruiters can click to validate.
For the complete guide on structuring your data engineer resume — including bullet formulas, ATS keywords, and templates by seniority level — see our Data Engineer Resume Guide.
List the certification with its full name (Fabric Data Engineer Associate) and exam code (DP-700) on your resume. Share the Credly badge on LinkedIn for a verified, clickable credential.
- Read the DP-700 study guide and mapped all skill statements to your knowledge level
- Completed the 5 official Microsoft Learn paths (~27 hours total)
- Practiced in a Microsoft Fabric trial workspace (built a lakehouse, ran a pipeline, wrote KQL queries)
- Scored 80%+ on the free Microsoft Learn practice assessment
- Tried the exam sandbox to familiarize yourself with interactive question types
- Reviewed KQL syntax for windowing functions and real-time analytics queries
- Know when to use Dataflow Gen2 vs. notebooks vs. pipelines
- Know the difference between workspace-level, item-level, and row/column-level security
- Scheduled the exam at least 1 week in advance
- Government-issued ID matches your Microsoft certification account name
Key Takeaways
- 1DP-700 replaced the retired DP-203 in March 2025. It is built entirely around Microsoft Fabric, not Azure Synapse.
- 2The exam has three equally weighted domains (30–35% each): implement/manage, ingest/transform, and monitor/optimize.
- 3It costs $165 USD, lasts 100 minutes, and requires a 700/1000 to pass. Renewal is annual but free.
- 4KQL (Kusto Query Language) and Real-Time Intelligence are the biggest new topics — allocate extra study time.
- 5Official Microsoft Learn paths are free and cover all exam content in ~27 hours of hands-on training.
- 6DP-700 is the right certification for engineers in the Microsoft ecosystem. AWS-heavy job markets should start with DEA-C01.
Frequently Asked Questions
Can I still take the DP-203 exam?
No. Microsoft retired DP-203 and the Azure Data Engineer Associate credential on March 31, 2025. The exam is no longer available, and the certification cannot be renewed. To earn a current Microsoft data engineering credential, you need to pass DP-700.
Does my DP-203 certification transfer to DP-700?
No. There is no automatic upgrade or transition path. If you held DP-203, it expired when the credential was retired. You need to pass DP-700 from scratch to earn the Fabric Data Engineer Associate certification.
Do I need Microsoft Fabric experience to pass DP-700?
Hands-on Fabric experience is strongly recommended. The exam tests practical decision-making — which storage option to use, how to troubleshoot a pipeline, when to choose a dataflow vs. a notebook. Microsoft offers a free Fabric trial that gives you full workspace access for studying.
How does DP-700 renewal work?
Microsoft associate certifications expire annually. About 6 months before expiration, you receive an email with a link to a free, unproctored online assessment on Microsoft Learn. Pass it before the expiration date, and your certification renews for another year — no exam fee required.
Should I get DP-700 or AWS DEA-C01 first?
Get the one that matches your target job market. If most postings mention Microsoft Fabric, Azure, or Power BI, get DP-700. If they mention AWS services (Glue, Redshift, S3), get AWS DEA-C01. Check 20–30 job listings for your target role and location to see which cloud dominates.
Is KQL hard to learn if I already know SQL?
KQL has a different syntax from SQL but the concepts overlap significantly. The biggest adjustment is the pipe-based query structure (table | where | project | summarize) instead of SQL's SELECT/FROM/WHERE. Most SQL-proficient engineers can become comfortable with KQL in 1–2 weeks of focused practice.
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Sources & References
- Microsoft Certified: Fabric Data Engineer Associate — Microsoft Learn (2026)
- Study Guide for Exam DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric — Microsoft Learn (2026)
- Exam Duration and Exam Experience — Microsoft Learn (2025)
- Designing Data-Intensive Applications — Martin Kleppmann (2017)