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AI Analytics
Dashboard

An intelligent analytics platform that processes 1M+ data points daily using machine learning. Built with real-time pipelines, predictive models, and natural language insights.

10 Weeks
Duration
ML Pipeline
Architecture
950+
Students Built
Live Demo View Source Code
Built with : React Python TensorFlow Docker
InsightAI Analytics
Predictions
96.4%
+2.1%
Data Points
1.2M
+18.4%
Anomalies
14
-6.3%
Model Accuracy Trend Last 7 Days
Revenue Forecast Model
#MODEL-0192
Active
v3.2
About This Project

Build an Intelligent
Analytics Engine

This is not a toy dashboard. You will build InsightAI — a full-scale analytics platform that ingests live data streams, trains predictive models, and surfaces insights through natural language and interactive visualizations.

Students architect this using ETL pipelines, implement ML models with Scikit-learn & TensorFlow, set up real-time streaming with Kafka, and deploy via Docker containers on AWS. The result? A portfolio piece that impresses senior data engineers.

By the end, you will have handled real-world challenges like feature engineering at scale, model drift detection, anomaly alerting pipelines, and automated retraining with CI/CD.

20+
API Endpoints
96%
Model Accuracy
<150ms
Inference Time
99.9%
Uptime SLA
ML Models
12+ trained models
Data Pipeline
Real-time streaming
Kafka ETL Spark
Anomaly Detection
Auto-alerting
Isolation Forest Alerts
NL Queries
Ask in plain English
Technology Stack

Enterprise-Grade Tech Stack

Every technology chosen for production readiness, scalability, and industry demand.

Frontend

Dashboard & Visualization Layer

React 18
Concurrent Features, Suspense
D3.js + Recharts
Advanced Data Visualization
Tailwind CSS
Utility-First Styling
Redux Toolkit + RTK Query
State Management & Caching

Backend

API & Business Logic

FastAPI
Async REST & WebSocket APIs
SQLAlchemy
ORM & Query Layer
JWT + OAuth2
AuthN & AuthZ
Apache Kafka
Real-Time Event Streaming

ML / AI Layer

Modeling & Inference

TensorFlow
Deep Learning Models
Scikit-learn
Classical ML Pipelines
Pandas + NumPy
Data Wrangling
MLflow
Experiment Tracking

Data Layer

Storage & Caching

PostgreSQL 15
Primary Relational DB
MongoDB
Raw Event & Log Store
Redis 7
Caching & Pub/Sub
AWS S3
Data Lake Storage

DevOps

Deployment & Infrastructure

Docker + Compose
Containerization
Kubernetes
Model & Service Orchestration
GitHub Actions
CI/CD Pipelines
AWS SageMaker
Model Training & Deployment

Testing

Quality Assurance

Pytest
Unit & Model Testing
Great Expectations
Data Quality Validation
Cypress + Jest
E2E & Component Tests
Postman Collections
API Contract Testing
Features

What You Will Build

Every feature mirrors real production systems used by companies like Google Analytics, Mixpanel, and Tableau.

Real-Time Data Ingestion

Kafka-based streaming pipeline that ingests events from multiple sources, transforms them, and feeds live dashboards without delay.

Kafka ETL

Predictive Analytics Engine

Time-series forecasting models trained on historical data to predict revenue, churn, and demand trends weeks in advance.

TensorFlow Forecasting

Anomaly Detection & Alerts

Isolation Forest-based anomaly detection flags unusual patterns in metrics in real time, with instant Slack/email alerts.

Isolation Forest Alerting

Natural Language Query

Ask questions in plain English like "show me last month's top regions" and get instant charts powered by an LLM query translator.

NLP LLM

Automated Report Builder

Drag-and-drop report designer that schedules and emails PDF/Excel analytics reports automatically to stakeholders.

Scheduler Export

Interactive Visual Dashboards

Fully customizable D3.js-powered dashboards with drill-down charts, heatmaps, and drag-to-resize widget layouts.

D3.js Widgets

Role-Based Dashboards

Custom views for executives, analysts, and admins with granular permission controls and saved dashboard layouts per role.

RBAC Custom Views

Model Monitoring & Drift Detection

MLflow-powered tracking of model performance in production with automated retraining triggers when accuracy drops.

MLflow Drift Detection

Third-Party Data Connectors

Pre-built connectors for Google Analytics, Salesforce, and Stripe to pull external data straight into the analytics engine.

Connectors Integrations
Screenshots

Project Gallery

A visual walkthrough of the platform's key interfaces and dashboards.

Dashboard Overview
View Screenshot

Dashboard Overview

Live KPI widgets, revenue charts, and traffic metrics on a single pane.

Predictive Analytics
View Screenshot

Predictive Analytics

Forecast charts with confidence intervals for revenue and demand.

Anomaly Detection
View Screenshot

Anomaly Detection

Real-time alerts highlighting unusual spikes and drops in metrics.

NLP Query Interface
View Screenshot

NLP Query Interface

Ask questions in plain English and get instant chart responses.

Report Builder
View Screenshot

Report Builder

Drag-and-drop scheduler for automated PDF and Excel reports.

Model Monitoring
View Screenshot

Model Monitoring

MLflow dashboard tracking accuracy, drift, and retraining status.

Architecture

System Architecture

Streaming-first architecture designed for real-time ingestion, ML inference, and horizontal scaling.

Client Layer

User-facing applications

React SPA
Dashboard UI
Admin Panel
Swagger UI

API Gateway Layer

Traffic management & security

Nginx
Rate Limiting
SSL/TLS
Load Balancer

Application & ML Services

Data processing and inference microservices

Ingestion Service
ML Inference
Analytics Service
Reporting Service

Data Layer

Storage, streaming & caching infrastructure

PostgreSQL
Redis
Kafka
AWS S3