Advanced Analytics & Business Intelligence Platform #202
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
@Ayaanshaikh12243 is attempting to deploy a commit to the Renu's projects Team on Vercel. A member of the Team first needs to authorize it. |
🎉 Thanks for the PR, @Ayaanshaikh12243!We really appreciate you taking the time to contribute to OpenPlayground! 💙 ⭐ Love this project?Please give us a star! It helps the project grow and reach more developers! 🌟 🔗 https://github.com/Renu-code123/ExpenseFlow ✅ PR ChecklistBefore we review, please ensure:
🙌 Thank You for Contributing!We truly appreciate your interest in contributing to this project.
We'll review your PR as soon as possible. Keep up the great work! ✨ |
Contributor
Author
|
@Renu-code123 please check mam and merge thank you |
|
The latest updates on your projects. Learn more about Vercel for GitHub.
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Advanced Analytics & Business Intelligence Platform
#196
📊 Key Components Implemented:
Backend Models:
DataWarehouse Model - Multi-dimensional time-series data with metrics, KPIs, trends, and predictions
CustomDashboard Model - Flexible dashboard configuration with widgets and visualizations
FinancialHealthScore Model - Comprehensive financial health assessment with risk analysis
Advanced Analytics Service:
Data Warehouse Engine - Automated aggregation across multiple time granularities
KPI Calculation System - Burn rate, runway, expense ratios, diversification index
Predictive Analytics - Expense/income forecasting with confidence intervals
Financial Health Scoring - Weighted scoring algorithm with risk assessment
Anomaly Detection - Statistical analysis for unusual spending patterns
API Endpoints:
Data Warehouse APIs - Historical analysis and metric retrieval
Dashboard Management - Custom dashboard creation and widget configuration
Predictive Analytics - Forecasting and trend analysis endpoints
Business Intelligence - KPI tracking and automated insights
Advanced Features:
Multi-Granularity Analytics - Daily, weekly, monthly, quarterly, yearly analysis
Custom Dashboard Builder - Drag-and-drop widgets with real-time data
Predictive Forecasting - 6-month expense/income predictions with ML algorithms
Financial Health Scoring - 100-point scoring system with risk assessment
Automated Insights - AI-generated recommendations and anomaly alerts
Benchmarking System - Industry comparisons and peer analysis
Business Intelligence Features:
KPI Dashboard - Real-time tracking of critical financial metrics
Trend Analysis - Growth rates, volatility, and seasonality detection
Risk Assessment - Multi-factor risk evaluation with mitigation strategies
Performance Benchmarking - Industry averages and historical comparisons
Export Capabilities - JSON, CSV, Excel formats for external analysis
Machine Learning Capabilities:
Time Series Forecasting - ARIMA-based expense prediction models
Anomaly Detection - Statistical outlier identification with confidence scoring
Pattern Recognition - Spending behavior analysis and categorization
Clustering Analysis - Expense grouping and trend identification
Technical Highlights:
Data Warehouse Architecture with optimized indexing and aggregation pipelines
Real-time Analytics with incremental updates and caching strategies
Predictive Models using statistical analysis and machine learning
Custom Visualization Engine with multiple chart types and interactive features
Performance Optimization with efficient queries and memory management
The system transforms ExpenseFlow into a comprehensive business intelligence platform, providing users with enterprise-grade analytics, predictive insights, and strategic financial intelligence for data-driven decision making.