A practical DEA-C01 study plan you can follow: 30-day intensive, 60-day balanced, and 90-day part-time schedules with weekly focus by domain, suggested hours/week, and tips for using the Mastery Cloud practice app.
This page answers the question most candidates actually have: “How do I structure my DEA‑C01 prep?”
Below are three realistic schedules (30/60/90 days) based on the official domain weights and the way DEA‑C01 questions are written (scenario + trade-offs + operational best practices).
Use the plan that matches your available time, then follow the loop: Syllabus → drills → review misses → mixed sets → timed runs.
Typical ranges based on background:
| Your starting point | Typical total study time | Best-fit timeline |
|---|---|---|
| You build data pipelines on AWS already | 40–60 hours | 30–60 days |
| You know data engineering but are newer to AWS services | 60–90 hours | 60–90 days |
| You’re newer to data platforms and analytics services | 90–120+ hours | 90 days |
Choose a plan based on hours per week:
| Time you can commit | Recommended plan | What it feels like |
|---|---|---|
| 10–15 hrs/week | 30‑day intensive | Fast learning + lots of practice |
| 6–9 hrs/week | 60‑day balanced | Steady progress + room for review |
| 3–5 hrs/week | 90‑day part‑time | Slow-and-solid with repetition |
DEA‑C01 domain weights:
| Domain | Weight | Prep focus |
|---|---|---|
| Domain 1: Data Ingestion and Transformation | 34% | Ingestion patterns, ETL/processing choices, orchestration |
| Domain 2: Data Store Management | 26% | Store selection, catalogs, lifecycle, modeling + schema evolution |
| Domain 3: Data Operations and Support | 22% | Automation, analytics, monitoring, data quality |
| Domain 4: Data Security and Governance | 18% | IAM/Lake Formation, encryption/masking, audit logs, privacy |
If you want one rule: spend ~60% learning + 40% practice early, then invert it to ~30% learning + 70% practice in the final 1–2 weeks.
Target pace: ~10–15 hours/week.
Goal: cover the blueprint quickly, then harden instincts through drills and mixed sets.
| Week | Focus (domains/tasks) | What to do | Links |
|---|---|---|---|
| 1 | Domain 1 foundations • Task 1.1 • Task 1.2 | Build ingestion + ETL service pickers (Kinesis/MSK/DMS/AppFlow; Glue/EMR/Lambda/Redshift). Do 2–3 focused drills and start a miss log. | Syllabus • Cheatsheet • Practice |
| 2 | Domain 1 orchestration + programming + start Domain 2 • Task 1.3 • Task 1.4 • Task 2.1 | Focus on orchestration trade-offs (MWAA vs Step Functions vs Glue workflows) + IaC/SQL basics. End the week with a 30–40Q mixed set. | Cheatsheet • Practice |
| 3 | Domain 2 store management + modeling • Task 2.2 • Task 2.3 • Task 2.4 | Catalog + partitions + lifecycle policies + schema evolution. Drill data format/partitioning questions until they feel automatic. | Syllabus • Practice |
| 4 | Domain 3 ops + Domain 4 governance + review • Task 3.1 • Task 3.2 • Task 3.3 • Task 3.4 • Task 4.1–Task 4.5 | Do 2 mixed sets + 1 timed run (65Q/130m). Review every miss and re-drill weak tasks until misses repeat less. | Practice • FAQ |
Target pace: ~6–9 hours/week.
Goal: spaced repetition and deeper drills while steadily building practice volume.
| Weeks | Focus | What to do |
|---|---|---|
| 1–2 | Domain 1 (Tasks 1.1–1.4) | Ingestion, ETL/processing, orchestration, SQL/IaC basics; do 2 drills per week. |
| 3–4 | Domain 2 (Tasks 2.1–2.4) | Store selection, catalog/partitions, lifecycle, modeling/schema evolution; end week 4 with a mixed set. |
| 5–6 | Domain 3 (Tasks 3.1–3.4) | Automation, analytics choices, monitoring, data quality; do weekly mixed sets. |
| 7–8 | Domain 4 (Tasks 4.1–4.5) + final review | IAM/Lake Formation, encryption, audit logs, privacy; 2 timed runs and re-drill weak tasks. |
Use task links from the Syllabus to drill each area as you go.
Target pace: ~3–5 hours/week.
Goal: slow repetition with consistent drills and periodic mixed sets.
| Week | Focus (tasks) | What to do |
|---|---|---|
| 1 | Task 1.1 | Batch vs streaming + triggers/schedules; do one drill set. |
| 2 | Task 1.2 | Glue vs EMR vs Redshift; drill. |
| 3 | Task 1.3 | MWAA vs Step Functions vs Glue workflows; drill. |
| 4 | Task 1.4 | SQL + IaC basics; drill. |
| 5 | Task 2.1 | Store selection + access patterns; drill. |
| 6 | Task 2.2 | Glue catalog + crawlers + partitions; drill. |
| 7 | Task 2.3 | Lifecycle + retention + TTL; do a mixed set. |
| 8 | Task 2.4 | Modeling + schema evolution; drill. |
| 9 | Task 3.1 | Automation + orchestration patterns; drill. |
| 10 | Task 3.2 | Athena/Redshift + QuickSight; drill. |
| 11 | Task 3.3 + Task 3.4 | Monitoring + data quality; drill. |
| 12 | Domain 4 (Tasks 4.1–4.5) + final review | Security/governance; 2 timed runs and re-drill weak tasks. |
Use the app to turn the syllabus into a repeatable loop:
Direct practice link: /app/cloud/#/topic-selection/aws_dea-c01