AI Wisdom

Amazon Web Services associate level

AWS Certified Data Engineer – Associate

Code
DEA-C01
Length
130 minutes
Pass mark
720 out of 1,000
Price
$150
Valid for
3 years. Renew by passing the latest version, passing AIP-C01, or through the maintenance option on AWS Skill Builder.
Study time, our estimate
60 to 90 hours

This is the data exam for AWS, and it is what most AI data engineers actually need. There is no ML training in scope. It covers getting clean, governed data to the right store at the right cost, and it now expects a general idea of vectors.

Take it if

You build the pipelines that feed AI systems on AWS.

Skip it if

You work on the model side. MLA covers that.

Before you start

Check yourself against this list first. If something is missing, close that gap before you pay for an exam.

  • Two to three years of data engineeringAWS recommends this.
  • One to two years on AWSHands-on, not reading.
  • SQL and GitBoth are assumed.

Next: MLA-C02

All exam details
Format
65 questions, 50 scored
Length
130 minutes
Pass mark
720 out of 1,000
Price
$150
Valid for
3 years. Renew by passing the latest version, passing AIP-C01, or through the maintenance option on AWS Skill Builder.
Delivery
Pearson VUE, test center or online
Experience
2 to 3 years in data engineering, 1 to 2 years on AWS
If you fail
Wait 14 days

What the exam covers

  • Data Ingestion and Transformation34%
  • Data Store Management26%
  • Data Operations and Support22%
  • Data Security and Governance18%

What to focus on

  • Streaming against batch ingestion: Kinesis, Firehose, Glue and Lambda.
  • Choosing a store and modeling it: S3, Redshift, DynamoDB, plus partitioning and file formats.
  • Orchestration: Step Functions, MWAA and Glue workflows.
  • Athena, data quality checks, and monitoring pipelines.
  • Lake Formation, KMS, IAM, and logging for audit.
Everything on one mapEvery topic and key idea in this certification.
mindmap
  root((DEA-C01))
    Ingestion and transformation
      Data Streams
      Firehose
      Glue
    Data stores
      File formats
      Redshift loads
      Lifecycle
    Operations
      Orchestration
      Data quality
      Monitoring
    Security and governance
      Lake Formation
      Encryption
      Audit

Lesson 1 of 4, 34% of the exam

Ingestion and transformation

The largest domain.

Data Streams
Several consumers, with replay during retention.
Firehose
Delivers streams to destinations with no consumer code.
Glue
Managed ETL and cataloging.
Which streaming service?Decide by who reads the stream.
flowchart TD
  A{"Do you need custom consumers or replay?"} -->|Yes| B["Kinesis Data Streams"]
  A -->|No, just deliver it| C["Amazon Data Firehose"]

Common trap

Picking Data Streams when no custom consumer is needed.

Try it yourself

Build one streaming and one batch pipeline into S3.

Official docs: Amazon Data FirehoseKinesis Data Streams

Lesson 2 of 4, 26% of the exam

Data stores

Storage choices set cost and speed.

File formats
Columnar formats and partitions reduce what Athena scans.
Redshift loads
COPY loads in parallel.
Lifecycle
S3 rules move old data to colder classes.
Why Parquet and partitions cost lessAthena pays for what it scans.
flowchart LR
  A["CSV, all columns"] --> B["Scans everything"]
  C["Parquet"] --> D["Reads needed columns"]
  E["Partitions"] --> F["Skips other folders"]
  D --> G["Lower scan cost"]
  F --> G

Common trap

Inserting row by row into Redshift.

Try it yourself

Convert CSV to partitioned Parquet and compare the Athena scan.

Official docs: Athena performance tuningRedshift COPYS3 Lifecycle

Lesson 3 of 4, 22% of the exam

Operations

Pipelines fail, so plan for it.

Orchestration
Step Functions and MWAA run multi-step work.
Data quality
Glue Data Quality checks rules inside pipelines.
Monitoring
Track failures and freshness.
Stop bad data earlyA quality gate protects everything downstream.
flowchart LR
  A["Ingest"] --> B["Transform"]
  B --> C{"Quality rules pass?"}
  C -->|Yes| D["Publish"]
  C -->|No| E["Quarantine and alert"]

Common trap

Finding bad data only after it reaches dashboards.

Try it yourself

Add a quality rule that stops a bad load.

Official docs: AWS Step FunctionsAWS Glue Data Quality

Lesson 4 of 4, 18% of the exam

Security and governance

Fine-grained access matters more with AI consumers.

Lake Formation
Central permissions, down to columns.
Encryption
KMS for data at rest.
Audit
Enable logging for access and changes.
Central data permissionsOne place to grant access to the lake.
flowchart LR
  A["Analyst"] --> B["Athena"]
  B --> C["Lake Formation check"]
  C --> D["Allowed columns only"]
  D --> E[("S3 data lake")]
  F["KMS"] -.->|"Decrypts"| E

Common trap

Managing table access with bucket policies.

Try it yourself

Limit one analyst to selected columns.

Official docs: AWS Lake Formation

Study plan

  1. Weeks 1 and 2: ingest

    Build one streaming and one batch pipeline into S3. Catalog the data with a Glue crawler.

  2. Week 3: store and query

    Convert to partitioned Parquet, query with Athena, load into Redshift, and compare scan costs.

  3. Week 4: operate and secure

    Orchestrate the pipeline, add data quality rules, then lock it down with Lake Formation and KMS.

  4. Exam week

    Do the official practice question set, then the mock below.

Exam day and after

  • Unanswered questions count as wrong and there is no penalty for guessing, so answer everything.
  • Scoring is compensatory. You need the overall score, not a pass in each domain.
  • Some questions are unscored and they are not marked, so do not read anything into a strange one.
  • After passing any AWS exam, you get 50% off your next one. A failed attempt means a 14-day wait, and every attempt is paid.
  • Many questions ask for the least operational overhead, which usually means the managed service.
Test yourself8 practice questions, scored by exam topic.
Start the mock exam

Keep going

Exam facts checked on October 31, 2026 against DEA-C01 official exam guide. Lessons are our own explanations, so use the official docs as the final word, and confirm price and dates before booking.