8.0 KiB
Implementation Readiness Assessment Report
Date: 2026-01-10 Project: Data_analysis
PRD Analysis
Functional Requirements
FR1: Users can upload datasets in .xlsx, .xls, and .csv formats via drag-and-drop or file selection. FR2: System automatically detects column data types (numeric, categorical, datetime) upon ingest. FR3: Users can manually override detected data types if the inference is incorrect. FR4: Users can rename columns directly in the interface to sanitize inputs. FR5: Users can view loaded data in a paginated, virtualized grid capable of displaying 50,000+ rows. FR6: Users can edit cell values directly (double-click to edit) with inputs validated against the column type. FR7: Users can sort columns (asc/desc) and filter rows based on values/conditions (e.g., "> 100"). FR8: Users can perform Undo/Redo operations (Ctrl+Z/Ctrl+Y) on data edits within the current session. FR9: Users can exclude specific rows from analysis without deleting them (soft delete/toggle). FR10: System automatically identifies univariate outliers using IQR/Z-score and visualizes them in the grid/plots. FR11: System automatically identifies multivariate outliers using Isolation Forest upon user request. FR12: Users can accept or reject outlier exclusion proposals individually or in bulk. FR13: Users can select a Target Variable (Y) to trigger an automated Feature Importance analysis. FR14: System recommends the Top-N predictive features based on RFE (Recursive Feature Elimination) or Random Forest importance. FR15: Users can configure a Linear Regression (Simple/Multiple) by selecting Dependent (Y) and Independent (X) variables. FR16: Users can configure a Binary Logistic Regression for categorical target variables. FR17: System generates a "Model Summary" including R-squared, Adjusted R-squared, F-statistic, and P-values for coefficients. FR18: System generates standard diagnostic plots: Residuals vs Fitted, Q-Q Plot, and Scale-Location. FR19: Users can view a Correlation Matrix (Heatmap) for selected numeric variables. FR20: Users can view an interactive "Analysis Report" dashboard summarizing data health, methodology, and model results. FR21: Users can export the full report as a branded PDF document. FR22: System appends an "Audit Trail" to the report listing library versions, random seeds, and data exclusion steps for reproducibility.
Total FRs: 22
Non-Functional Requirements
NFR1: Grid Latency: render 50,000 rows with filtering/sorting response times under 200ms. NFR2: Analysis Throughput: Automated analysis on standard datasets (<10MB) must complete in under 15 seconds. NFR3: Upload Speed: Parsing and validation of a 5MB Excel file should complete in under 3 seconds. NFR4: Data Ephemerality: All user datasets purged after 1 hour of inactivity or session termination. NFR5: Transport Security: Data transmission must be encrypted via TLS 1.3. NFR6: Input Sanitization: File parser must validate MIME types and signatures to prevent macro execution. NFR7: Graceful Degradation: Handle NaNs/infinite values with clear error messages instead of crashing. NFR8: Concurrency: Support at least 50 concurrent analysis requests using an asynchronous task queue. NFR9: Keyboard Navigation: Data grid must be fully navigable via keyboard.
Total NFRs: 9
Additional Requirements
- Stateless Architecture: Phase 1 requires no persistent user data storage.
- Scientific Rigor: Reproducibility of results is paramount (Trace d'Analyse).
- Desktop Only: Strictly optimized for high-resolution desktop displays.
PRD Completeness Assessment
The PRD is exceptionally comprehensive, providing numbered, testable requirements (FR1-FR22) and specific, measurable quality attributes (NFR1-NFR9). The "Experience MVP" strategy is clearly defined, and the project context (Scientific Greenfield) is well-articulated. No major gaps were identified during extraction.
Epic Coverage Validation
FR Coverage Analysis
| FR Number | PRD Requirement | Epic Coverage | Status |
|---|---|---|---|
| FR1 | Upload datasets (.xlsx, .xls, .csv) | Epic 1 Story 1.2 | ✓ Covered |
| FR2 | Auto-detect column data types | Epic 1 Story 1.2 | ✓ Covered |
| FR3 | Manual type override | Epic 1 Story 1.4 | ✓ Covered |
| FR4 | Rename columns | Epic 1 Story 1.4 | ✓ Covered |
| FR5 | High-performance grid (50k+ rows) | Epic 1 Story 1.3 | ✓ Covered |
| FR6 | Edit cell values directly | Epic 2 Story 2.1 | ✓ Covered |
| FR7 | Sort and filter rows | Epic 1 Story 1.5 | ✓ Covered |
| FR8 | Undo/Redo operations | Epic 2 Story 2.2 | ✓ Covered |
| FR9 | Exclude rows (soft delete) | Epic 2 Story 2.5 | ✓ Covered |
| FR10 | Univariate outlier detection (IQR) | Epic 2 Story 2.3 | ✓ Covered |
| FR11 | Multivariate outlier detection (Isolation Forest) | Epic 2 Story 2.3 | ✓ Covered |
| FR12 | Outlier review UI (Insight Panel) | Epic 2 Story 2.4 | ✓ Covered |
| FR13 | Feature Importance analysis | Epic 3 Story 3.2 | ✓ Covered |
| FR14 | Top-N predictive feature recommendations | Epic 3 Story 3.3 | ✓ Covered |
| FR15 | Linear Regression configuration | Epic 4 Story 4.1 | ✓ Covered |
| FR16 | Logistic Regression configuration | Epic 4 Story 4.1 | ✓ Covered |
| FR17 | Model Summary (R², P-values, etc.) | Epic 4 Story 4.2 | ✓ Covered |
| FR18 | Diagnostic plots | Epic 4 Story 4.3 | ✓ Covered |
| FR19 | Correlation Matrix (Heatmap) | Epic 3 Story 3.1 | ✓ Covered |
| FR20 | Analysis Report dashboard | Epic 4 Story 4.3 | ✓ Covered |
| FR21 | Export branded PDF | Epic 4 Story 4.4 | ✓ Covered |
| FR22 | Reproducibility Audit Trail | Epic 4 Story 4.4 | ✓ Covered |
Missing Requirements
None. All 22 Functional Requirements from the PRD are mapped to specific stories in the epics document.
Coverage Statistics
- Total PRD FRs: 22
- FRs covered in epics: 22
- Coverage percentage: 100%
UX Alignment Assessment
UX Document Status
- Found:
_bmad-output/planning-artifacts/ux-design-specification.md
Alignment Analysis
UX ↔ PRD Alignment:
- ✅ User Journeys: Optimized for identified personas (Julien & Marc).
- ✅ Feature Coverage: 100% of FRs have defined interaction patterns.
- ✅ Workflow: Assisted analysis loop matches the PRD vision.
UX ↔ Architecture Alignment:
- ✅ Performance: High-density grid requirements supported by Apache Arrow stack.
- ✅ State Management: Zustand choice supports high-frequency UI updates.
- ✅ Responsive Strategy: Consistent "Desktop Only" approach across all plans.
Warnings
- None.
Epic Quality Review
Epic Structure Validation
- ✅ Epic 1: Ingestion - Focused on user value.
- ✅ Epic 2: Hygiene - Standalone value, no forward dependencies.
- ✅ Epic 3: Smart Prep - Incremental enhancement.
- ✅ Epic 4: Modélisation - Final completion of journey.
Story Quality & Sizing
- ✅ Story 1.1: Correctly initializes project from Architecture boilerplate.
- ✅ Acceptance Criteria: All stories follow Given/When/Then format.
- ✅ Story Sizing: Optimized for single agent dev sessions.
Dependency Analysis
- ✅ No Forward Dependencies: No story depends on work from a future epic.
- ✅ Database Timing: Stateless logic introduced exactly when required.
Quality Assessment Documentation
- 🔴 Critical Violations: None.
- 🟠 Major Issues: None.
- 🟡 Minor Concerns: None.
Summary and Recommendations
Overall Readiness Status
READY ✅
Critical Issues Requiring Immediate Action
- None.
Recommended Next Steps
- Initialize Project: Run
docker-compose upto verify the monorepo skeleton (Epic 1 Story 1.1). - Performance Spike: Validate Apache Arrow streaming with a 50k row dataset early in development.
- UI Setup: Configure the Shadcn UI ThemeProvider for native Dark Mode support from the start.
Final Note
This assessment identifies 0 issues. The project planning is complete, coherent, and highly robust. You may proceed immediately to implementation.