Work

Real-time Analytics Dashboard

Angular
NodeJS
MySQL
D3.js
WebSockets

Created a real-time analytics dashboard for sales teams that processes and visualizes customer data from multiple sources with customizable reports.

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Project Overview

In this project, I designed and developed a comprehensive real-time analytics dashboard for the company’s sales teams. The dashboard provides intuitive visualizations of customer data from multiple sources, enabling sales representatives and managers to make data-driven decisions quickly and effectively.

Technical Challenge

The main challenges included:

  • Integrating data from disparate sources (CRM, ERP, marketing platforms) in real-time
  • Designing an intuitive interface that presents complex data in an accessible way
  • Ensuring high performance with large datasets and concurrent users
  • Implementing customizable reports and visualizations for different user roles
  • Maintaining data accuracy and consistency across all views

Solution

I developed a full-stack solution that included:

  • Angular frontend with responsive design and interactive visualizations
  • NodeJS backend with RESTful APIs and WebSocket connections
  • MySQL database with optimized queries and indexing
  • D3.js for custom, interactive data visualizations
  • Real-time data processing pipeline with WebSockets
  • Role-based access control and customizable dashboards

Implementation Details

Frontend Architecture

The dashboard was built with Angular using a modular component architecture:

  • Reusable visualization components (charts, tables, KPI cards)
  • Drag-and-drop dashboard customization
  • Responsive design for desktop and tablet use
  • Theme customization and accessibility features
  • Advanced filtering and data exploration tools

Real-time Data Processing

To achieve real-time updates, I implemented:

  • WebSocket connections for live data streaming
  • Efficient data transformation and aggregation on the server
  • Client-side caching to reduce server load
  • Optimized rendering to handle frequent updates
  • Fallback mechanisms for offline operation

Reporting Engine

The custom reporting engine allowed users to:

  • Create and save report templates
  • Schedule automated report generation
  • Export data in multiple formats (PDF, Excel, CSV)
  • Share reports with team members
  • Set up alerts based on custom thresholds

Results

The analytics dashboard delivered significant business value:

  • 35% increase in sales team productivity
  • 28% improvement in lead conversion rates
  • 50% reduction in time spent creating reports
  • Enhanced visibility into sales pipeline and customer behavior
  • Data-driven decision making across all levels of the organization

This project demonstrates my ability to design and implement complex, data-intensive applications that deliver tangible business results. The dashboard continues to evolve with new features and integrations based on user feedback and changing business requirements.