DACO study plan

Define data governance and articulate its difference from data management and IT governance in your own written summary

Map the core governance components (policy, standards, stewardship, decision rights, operating model) onto a one-page diagram

Identify the roles of data owner, data steward, data custodian, and CDO, and write a two-sentence responsibility statement for each

Draft a RACI for a data issue escalation path covering business, IT, and compliance stakeholders

Write a data strategy statement linking three business objectives to measurable data capabilities

Classify a sample of 15 data assets against a maturity model and justify each score in one line

Compare conceptual, logical, and physical model levels and produce one small example of each for a customer entity

Explain the purpose of a data architecture blueprint and list the artifacts it typically contains

Apply normalization rules through third normal form to a denormalized order dataset and document each decomposition step

Design a dimensional model with one fact table and three conformed dimensions, naming grain and degenerate dimensions explicitly

Distinguish star, snowflake, and data vault approaches and state one use case where each is preferable

Define reference data, master data, and metadata categories and give two concrete examples of each

Compare row-store, column-store, and key-value storage engines on read/write patterns and select one for three stated workloads

Explain ACID versus BASE trade-offs and map isolation levels to two concrete anomaly scenarios

Describe partitioning, sharding, and indexing strategies and predict their effect on a given query pattern

Outline backup, recovery, and capacity-planning activities in a database operations runbook

Classify data into sensitivity tiers and assign handling rules to each tier

Map three regulatory obligations (for example privacy, breach notification, retention) to specific technical controls

Apply role-based and attribute-based access control designs to a multi-tenant scenario and justify the choice

Describe encryption at rest, in transit, and tokenization, and state where each control belongs in the data lifecycle

Draft an incident response sequence for a suspected data breach from detection to notification

Compare batch, streaming, and change-data-capture integration patterns and match each to a stated latency requirement

Design an interface contract specifying schema, keys, nullability, and error handling for one data feed

Explain idempotency, exactly-once versus at-least-once delivery, and how to reconcile duplicates downstream

Identify interoperability standards relevant to your sector and note where semantic versus syntactic integration differs

Trace one record from source to consumption and document transformation and lineage at each hop

Define six data quality dimensions and write a testable rule for each against a sample dataset

Design a data quality scorecard with thresholds, owners, and remediation triggers

Distinguish descriptive, diagnostic, predictive, and prescriptive analytics and match each to a business question

Explain how data profiling and root-cause analysis reduce defect recurrence

Describe how metadata and lineage support trustworthy analytics and audit

Synthesize all six domains into a single integrated case study covering governance, architecture, storage, security, integration, and quality decisions

Complete a timed 60-question practice set and categorize every miss by domain and root cause

Re-teach your three weakest concepts in writing without notes to confirm retention

Build a one-page exam-day reference sheet of frameworks, trade-offs, and definitions