All 8 domains
46 official practical applications
70–100 hrs suggested study
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Domain 01
25%
The heaviest ABDE domain covers how raw data from databases, APIs and files becomes trustworthy, analysis-ready tables. Get ingestion choices right here and most storage, orchestration and governance questions become easier to reason through.
Inside this domain
- Implementing ETL/ELT pipelines
- Data cleansing and normalization
- Handling batch and real-time acquisition
- Managing schema evolution
- and 1 more practical applications
Watch for Real-time by default
- Practical applications
- 5
Read the domain guide →
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Domain 02
20%
Storage design decides what every query costs and how fast it runs. This 20% domain tests warehouse and lake architecture, partitioning, file formats, retention tiers and the tuning choices that keep big tables fast and affordable.
Inside this domain
- Creating data warehouse/lake architectures
- Implementing storage optimization strategies
- Setting up partitioning and indexing
- Managing data lifecycle and retention policies
- and 2 more practical applications
Watch for Most selective partition key
- Practical applications
- 6
Read the domain guide →
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Domain 03
15%
Pipelines that run by hand eventually fail silently. This 15% domain tests how you schedule, chain, observe and recover data workflows with Apache Airflow so that data arrives complete and on time.
Inside this domain
- Workflow scheduling and triggering
- Complex dependency management
- Comprehensive monitoring and alerting
- Implementing error handling and recovery mechanisms
- and 2 more practical applications
Watch for Schedule it later
- Practical applications
- 6
Read the domain guide →
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Domain 04
15%
Secure, trustworthy data is what makes a platform usable. This 15% domain tests access control, encryption, regulatory compliance, data quality validation, metadata catalogs and lineage, the controls that let people rely on what pipelines deliver.
Inside this domain
- Implementing access control and authentication systems
- Configuring data encryption
- Ensuring regulatory compliance
- Establishing data quality validation frameworks
- and 2 more practical applications
Watch for Encryption fixes everything
- Practical applications
- 6
Read the domain guide →
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Domain 05
10%
Good models make data easy to query and hard to misuse. This 10% domain tests dimensional modeling, logical and physical design, system architecture, technology selection, data mesh and fabric, and how schemas evolve without breaking consumers.
Inside this domain
- Creating dimensional models
- Developing logical and physical data models
- Designing overall system architecture
- Making technology selection decisions
- and 2 more practical applications
Watch for Normalize everything
- Practical applications
- 6
Read the domain guide →
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Domain 06
5%
Some decisions cannot wait for a nightly batch. This 5% domain tests how streaming pipelines capture, process and deliver continuous data with Apache Kafka and stream processors, and how they stay correct when events arrive late, twice or out of order.
Inside this domain
- Implementing streaming pipelines
- Stream processing frameworks
- Message brokers
- Building resilient real-time data flows
Watch for More consumers, more speed
- Practical applications
- 4
Read the domain guide →
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Domain 07
5%
Models are only as reliable as the data feeding them. This 5% domain tests the data engineer's side of machine learning: feature stores, ML pipeline integration, deployment data, training and inference datasets, and the feeds that let teams monitor models in production.
Inside this domain
- Implementing feature stores
- Integrating with ML pipelines
- Creating data infrastructure for model deployment
- Formatting data for AI-specific needs
- and 2 more practical applications
Watch for Blame the algorithm
- Practical applications
- 6
Read the domain guide →
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Domain 08
5%
LLM applications are only as good as the data they retrieve. This 5% domain tests the data systems behind generative AI: vector databases, embedding pipelines, retrieval augmented generation, fine-tuning data, prompt management, semantic search and token costs.
Inside this domain
- Implementing vector database solutions
- Creating embedding generation pipelines
- Building RAG (Retrieval Augmented Generation) systems
- Preparing data for LLM fine-tuning
- and 3 more practical applications
Watch for Fine-tune for fresh facts
- Practical applications
- 7
Read the domain guide →
Domain names, weights and practical applications come from DASCA's official outline (DASCA ABDE exam coverage, eight-domain DASCA-EKF structure (dasca.org, current as of October 2026; no version number or effective date published)). Question counts and study hours are editorial planning estimates, not official figures. Last reviewed October 2026.