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Development of a Scalable and Cost-Effective Analytics System for an IT eLearning Platform

nan-labs.com

Education

Information technology

Challenges with Existing Analytics System

The existing analytics system faced scalability limitations, high maintenance costs, and inefficiencies in handling millions of daily events from thousands of simultaneous users. The legacy infrastructure could not support the platform's growth or provide actionable insights for performance optimization.

About the Client

A B2B IT eLearning platform offering hands-on technical training and certifications to professionals.

Objectives for the New Analytics System

Design a scalable and cost-efficient analytics architecture
Process and analyze millions of events daily
Enable seamless integration with existing platform components
Support future system upgrades and enhancements
Implement robust logging for actionable insights

Core System Functionalities

Real-time data streaming via AWS Kinesis & Firehose
Scalable data storage using Elasticsearch & TimescaleDB
Interactive data exploration with Apache Zeppelin
Infrastructure-as-Code (IaC) deployment via AWS CloudFormation & Terraform
Automated log collection and analysis capabilities

Technology Stack Requirements

AWS Kinesis

AWS Firehose

Elasticsearch

TimescaleDB

Apache Zeppelin

Python

AWS CloudFormation

Terraform

System Integration Needs

Existing eLearning platform components
User activity tracking systems
Certification progress monitoring tools

Operational Requirements

High scalability for concurrent users
Cost-efficient resource utilization
99.9% system availability
Data security compliance
Low-latency processing for real-time analytics

Expected Business Impact

A state-of-the-art analytics system capable of handling millions of daily events with 40% reduced infrastructure costs, enabling data-driven platform optimizations and supporting 300% growth in user capacity while maintaining performance standards.