Certified Decision-Grade Data Analyst (CDDA)
Duration: 16 Weeks | Tools: Excel, SQL, Python, Power BI
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The Certified Decision-Grade Data Analyst (CDDA) program develops professionals capable of reasoning through ambiguous business and policy problems, executing defensible analytics, and standing behind recommendations under scrutiny. Certification is awarded only on demonstrated mastery, not attendance or tool exposure.
🎯 Program Aims
- Develop analysts capable of producing decision-grade, not descriptive, analytics
- Strengthen analytical reasoning and judgment prior to advanced tool usage
- Build statistically informed, risk-aware decision-making capability
- Enable learners to execute complete analytics workflows on real, imperfect data
- Produce professionals who can credibly defend analytical conclusions to executives, policymakers, and oversight bodies
🎓 Learning Outcomes
Upon successful certification, graduates will be able to:
- Frame ambiguous business, policy, and development problems into analyzable decision questions
- Identify relevant, missing, biased, and unreliable data
- Select and justify appropriate analytical methods and metrics
- Execute data auditing, cleaning, analysis, and validation workflows
- Build interpretable models and dashboards aligned to decision needs
- Communicate findings clearly, transparently, and defensibly
- Demonstrate professional judgment, ethical awareness, and risk sensitivity
🚪 Entry Requirements & Diagnostic Placement (Gate 0)
All applicants must complete a Scenario-Based Diagnostic Assessment prior to admission.
Placement Outcomes:
- Direct progression to Gate 1
- Conditional progression with mandatory remediation
- Deferred entry into foundation analytics track
No learner may bypass Gate 0 under any circumstances.
📚 Curriculum Structure
Gate 1: Analytical Foundations & Decision Reasoning
Duration: 4–6 Weeks
Purpose: To establish strong analytical reasoning, statistical thinking, and decision logic independent of tools.
Core Modules:
- Decision Problems, Contexts, and Stakeholder Needs
- Data Literacy, Interpretation, and Evidence Quality
- Statistical Reasoning for Decisions (variation, bias, uncertainty)
- Metric Selection, KPI Logic, and Measurement Risk
- Assumptions, Trade-offs, Ethics, and Professional Judgment
- Excel for Analytical Reasoning, Validation, and Auditability
Assessment Method: Scenario-based written evaluations
Pass Requirement: ≥75% overall and ≥50% in Analytical Reasoning
Gate 2: Core Analytics with Real-World Data
Duration: 6–8 Weeks
Purpose: To validate the learner’s ability to execute complete analytics workflows using imperfect real-world datasets.
Core Modules:
- Data Auditing and Quality Assessment
- Data Cleaning and Transformation (Excel, SQL, Python)
- Analytics Pipeline Logic and Reproducibility
- Applied Statistics for Analytics
- Exploratory, Diagnostic, and Predictive Analytics Foundations
- Power BI Data Modeling and DAX Fundamentals
Assessment Method: Case-based analytics projects with resubmissions until mastery
Gate 3: Decision Defense & Analytical Communication
Duration: 2–4 Weeks
Purpose: To ensure learners can credibly defend analytics-driven decisions to non-technical stakeholders.
Core Modules:
- Executive Communication for Analysts
- Analytical Storytelling and Insight Framing
- Risk, Uncertainty, and Limitations Disclosure
- Dashboard Interpretation and Misuse Prevention
Assessment Method: Live panel defense of analysis and recommendations
Outcomes: Pass | Conditional Pass | Re-defense Required
Gate 4: Professional Portfolio & Certification
Duration: 4–8 Weeks
Purpose: To confirm job readiness and award certification based solely on demonstrated competence.
Portfolio Requirements:
- Minimum of three completed real-world analytics projects
- Clear documentation, assumptions, and version history
- Business or policy decision context framing
- At least one publishable paper in the Awake to Power Journal of Productivity & Innovation (AJPI)
Assessment Method: Portfolio review by Certification Panel
Certification Rule: All criteria must be met. No partial certifications issued.
🏫 Teaching & Learning Methods
- Scenario-based decision analytics
- Real-world business and public-sector case studies
- Guided analytics workshops
- Mentorship and structured feedback
- Independent decision-grade analytics projects
🛡️ Certification Positioning Statement
The CDDA certification signifies that the holder can:
- Think before modeling
- Measure what matters
- Diagnose before predicting
- Communicate risk and uncertainty honestly
- Defend analytics under executive and policy scrutiny
This certification is aligned with expectations for Business Intelligence Analysts, Policy Analysts, Research Analysts, M&E Specialists, and Strategy Analysts across private sector, public sector, and development environments.