DMLI study plan

DMLI · Give each week a clear focus.

8 weeks · About 7 hours per week

Week 1

Data Management Fundamentals

Define each core data-management concept (data lifecycle, data vs. information, structured/unstructured data) in original one-sentence definitions
Diagram the data lifecycle from capture through archival and disposal, labeling the control point at each stage
Compare relational, dimensional, and NoSQL storage models on three criteria: integrity, scalability, and query flexibility
Map the DAMA-style data-management knowledge areas to the six exam domains and note overlaps

A one-page concept map of Domain 1 with every term defined in your own words and no unresolved blanks.

Week 2

Classify ten sample organizational policies as governance, compliance, or security controls
Explain the roles of data owner, steward, and custodian using a worked example of a single customer record
Outline a data-retention schedule for three record types, citing the risk of over- and under-retention
Describe how privacy regulations (e.g., consent, purpose limitation, data-subject rights) shape data-handling procedures
Draft a one-paragraph escalation path for a suspected data breach

A governance one-pager containing a RACI-style role table and a retention schedule for three record types.

Week 3

Integrate Domain 1 lifecycle stages with Domain 2 controls by assigning one governance control to each lifecycle stage
Produce five original multiple-choice questions that combine a Domain 1 concept with a Domain 2 compliance scenario
Identify three conflict points between operational data needs and compliance obligations and propose a resolution for each

A 15-question self-written practice set covering Domains 1–2, with answer rationales for each option.

Week 4

Define six data-quality dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness) and give a measurable test for each
Compare batch, streaming, and change-data-capture integration patterns on latency, cost, and complexity
Diagnose three common integration failure modes (duplicate keys, schema drift, late-arriving data) and prescribe a fix for each
Design a data-quality scorecard with thresholds and an owner for each metric

A data-quality scorecard template populated with six metrics, thresholds, and remediation owners.

Week 5

Build a normalized (3NF) logical model for a small business scenario and then derive a star-schema version of the same data
Justify each modeling choice (normalization vs. denormalization) against the intended analytical workload
Sketch a layered architecture (source, integration, warehouse, presentation) and state the purpose of each layer
List three trade-offs between a data lake and a data warehouse for a given reporting requirement

A two-diagram portfolio (3NF logical model and star schema) with a written rationale for every design decision.

Week 6

Distinguish descriptive, diagnostic, predictive, and prescriptive analytics with an original example of each
Select the appropriate chart type for five analytical questions and justify each selection
Identify three ways a visualization can mislead (truncated axes, cherry-picked time windows, misleading aggregation) and state the corrective practice
Write the requirements for one KPI, including definition, formula, source, and refresh cadence

A one-page BI brief defining one KPI end-to-end plus a mock dashboard wireframe with annotated chart choices.

Week 7

Apply a five-step ethical decision framework to two data scenarios (secondary use of data, algorithmic bias)
Describe how to communicate a data limitation to a non-technical stakeholder in plain language
Outline the components of a data-strategy pitch: problem, evidence, proposed action, and success measure
List three professional-practice obligations (documentation, reproducibility, conflict-of-interest disclosure) and give an example of each

A written ethics case analysis (one scenario) using the five-step framework, ending with a defensible recommendation.

Week 8

Re-take the Domains 1–2 practice set from week 3 and score at least 80%
Write and answer 30 mixed-domain questions weighted to match the exam percentages
Review every missed question, tagging the root cause as knowledge gap, misread, or process error
Compile a one-page formula and definitions sheet for last-minute review

A full-length 60-question mock exam with a scored answer key and a root-cause log of every error.

Week 2: Can define all Domain 1 core terms from memory and explain the owner/steward/custodian distinction without notes.

Week 4: Scores at least 75% on the 15-question Domains 1–2 set and can name a measurable test for all six data-quality dimensions.

Week 6: Produces both the 3NF and star-schema diagrams unaided and justifies each design choice in under five minutes of explanation.

Week 8: Scores at least 80% on the 60-question mock exam with no domain scoring below 70%.