Adobe Analytics Architect Master study plan
Adobe Analytics Architect Master · Give each week a clear focus.
8 weeks · About 7 hours per week
Solution design and technical discovery & Implementation strategy and variable/tag design
Draft a solution design document (SDD) skeleton covering business objectives, KPIs, audiences, and reporting surfaces for a hypothetical client
Translate five business questions into a proposed report suite structure and variable map (eVars, props, events) with naming conventions
Write a technical discovery questionnaire covering existing tags, data sources, integrations, and consent posture
Define a naming and ID convention standard for variables, events, and list props and justify each rule
Your checkpoint
A 4-6 page solution design document with variable map table and discovery questionnaire
Implementation strategy and variable/tag design & Data collection, tagging, and tracking architecture
Build a variable allocation plan that assigns every proposed dimension and metric to a specific variable type with expiry and allocation settings
Diagram the page-load, interaction, and app-lifecycle tracking flows including which calls fire on which events
Compare client-side vs. server-side and SDK-based collection approaches and select one with written rationale
Specify link tracking, download/exit tracking, and campaign tracking parameters with concrete examples
Your checkpoint
A tracking architecture diagram plus a completed variable allocation spreadsheet with expiry/allocation columns
Data collection, tagging, and tracking architecture & Data layer and integration architecture
Design a data layer specification (field names, types, nesting, ownership, population timing) for at least 25 fields
Map each data layer field to its destination Analytics variable and document fallback behavior when a field is absent
Write implementation pseudocode showing how the tag manager reads the data layer and sets variables before the beacon fires
Identify three integration use cases (CRM, warehouse, personalization) and specify the data exchange method for each
Your checkpoint
A data layer specification document with field-to-variable mapping table and integration notes
Processing rules, classifications, and data governance & Implementation strategy and variable/tag design
Author processing rules for at least 8 scenarios (lowercasing, concatenation, fallback values, bot filtering) and predict their effect on sample hits
Design a classification hierarchy for campaign and product dimensions including a key-lookup strategy
Document a data governance model naming data stewards, change control, and variable deprecation process
Audit your week 2 variable plan against processing-rule and classification constraints and revise it
Your checkpoint
A processing rules and classifications runbook with before/after hit examples
Segmentation, calculated metrics, and virtual report suites & Processing rules, classifications, and data governance
Build a segment logic matrix defining at least 10 segments with container scope, sequence requirements, and exclusions
Design 5 calculated metrics and verify the formula and format for each against a described reporting need
Plan two virtual report suites with distinct data views, filters, and permissions and justify each inclusion rule
Explain how segment and VRS design interacts with processing rules and classifications to avoid data leakage
Your checkpoint
A segmentation and calculated metrics catalog with formulas, scope, and intended consumer
Data governance, privacy, and compliance & Data layer and integration architecture
Map the organization's data categories to consent and retention requirements and produce a data classification table
Specify where consent state is captured, how it gates collection, and how opt-out propagates to downstream integrations
Draft a data retention and deletion workflow covering report suites, classifications, and exported datasets
Review the data layer design from week 3 against privacy requirements and list required changes
Your checkpoint
A privacy and compliance control matrix mapping each data category to its collection, consent, and retention control
Troubleshooting, validation, and quality assurance & Data collection, tagging, and tracking architecture
Write a validation test plan covering beacon inspection, variable values, data layer state, and processing-rule output for 15 test cases
Diagnose five realistic tracking defects from symptom descriptions and record the root cause and fix for each
Define a pre-release QA checklist and a post-release data-quality monitoring routine with thresholds
Reconcile a sample day of Analytics data against a second source and document discrepancies
Your checkpoint
A QA test plan and defect-triage log with 15 test cases and 5 worked diagnoses
Stakeholder communication and enablement & Solution design and technical discovery & Segmentation, calculated metrics, and virtual report suites
Create a one-page architecture summary and a stakeholder-ready enablement deck outline for non-technical audiences
Write a training quick-reference covering segment creation, VRS usage, and metric interpretation for business users
Run a full timed practice assessment across all domains and score each domain separately
Revisit the weakest two domains from the practice score and close the gaps with targeted review notes
Your checkpoint
An enablement package (architecture one-pager, training quick-reference, scored practice results with remediation notes)
Milestones
Week 2: Can explain, without notes, why each variable in your map uses its assigned type, expiry, and allocation setting
Week 4: Can trace a single user action from data layer push through tag firing, processing rules, and classification to a final report value
Week 6: Can describe how a consent opt-out stops collection and how that data is excluded or deleted downstream
Week 8: Scores at or above 80% overall on the timed practice assessment with no domain below 70%