DACO study guide

DACO · Work through your exam, one topic at a time.

The DACO credential is aimed at data practitioners who want to demonstrate that they can run data work as a governed, architected, and measurable discipline rather than a series of ad hoc projects. It suits data analysts moving into lead or architect roles, data stewards and governance officers, BI and platform engineers, and consultants who advise clients on data programmes. The DACO study guide has 6 sections and about 2,704 words.

Data Governance and Strategy

Data Governance and Strategy tests how an organization assigns decision rights and accountability for data, and how it converts business strategy into a funded, sequenced data roadmap. Expect questions that ask you to separate governance from management, place artifacts at the right level, and choose an operating model that fits the organization.

493 words, about 2 min 02

Data Architecture and Modeling

Data Architecture and Modeling tests whether you can connect enterprise architecture to concrete models: choosing abstraction levels, declaring grain, normalizing for integrity, and dimensionalizing for analytics. Questions often present a model defect and ask for the smallest correct fix.

435 words, about 2 min 03

Data Storage and Operations

Data Storage and Operations covers the physical and operational side: choosing storage engines, designing for recovery, and running databases reliably. The exam tests trade-offs such as row versus columnar, indexing, partitioning, and backup and recovery objectives, and whether you can reason from a stated requirement to a defensible design.

444 words, about 2 min 04

Data Security and Privacy

Data Security and Privacy tests controls that protect data and controls that limit its use lawfully. Questions pair a data classification with a control set such as masking, encryption, or access models, and check whether you can distinguish anonymization from pseudonymization and prevention from detection.

430 words, about 2 min 05

Data Integration and Interoperability

Data Integration and Interoperability tests how data moves and converges: batch or streaming, push or pull, ETL or ELT, and how conflicting sources are resolved into one trusted record. Expect scenarios on change data capture, idempotency, schema evolution, and master data survivorship.

449 words, about 2 min 06

Data Quality and Analytics

Data Quality and Analytics tests whether you can define quality measurably, find root causes rather than patch reports, and choose analytic methods that match the question. Expect scenarios on quality dimensions, rules and scorecards, and on interpretation errors such as aggregation and sampling bias.

453 words, about 2 min