Real-Time Learner Engagement Analytics Platform Development

Medium Priority
Data Engineering
Online Learning
👁️11563 views
💬434 quotes
$15k - $50k
Timeline: 8-12 weeks

Our scale-up company seeks an experienced data engineering consultant to develop a real-time learner engagement analytics platform. This platform will leverage modern data infrastructure to provide actionable insights into learner behaviors and preferences, enabling us to enhance our course offerings and improve student outcomes. We aim to integrate real-time data processing and analytics to stay competitive in the rapidly evolving online learning space.

📋Project Details

As a leading player in the Online Learning & MOOCs industry, we are committed to providing high-quality, personalized learning experiences. To achieve this, we need to invest in a robust, real-time analytics platform capable of processing extensive learner data. We are looking to harness the power of Apache Kafka for event streaming and Spark for real-time data processing. The project will also involve using Airflow for orchestrating data workflows, dbt for data transformations, and Snowflake or BigQuery for data warehousing. Additionally, we aim to implement MLOps practices to integrate machine learning models that can predict learner engagement patterns. This initiative is crucial to understanding and adapting to learner needs quickly, ensuring that our content remains relevant and engaging. This project is expected to be completed within an 8-12 weeks timeline, with a budget ranging from $15,000 to $50,000. We are particularly interested in consultants with a strong background in data mesh architectures and data observability practices.

Requirements

  • Experience with real-time data processing
  • Proficiency in data mesh architecture
  • Expertise in MLOps and data observability
  • Ability to integrate with Apache Kafka and Spark
  • Familiarity with data warehousing solutions like Snowflake or BigQuery

🛠️Skills Required

Apache Kafka
Spark
Airflow
dbt
Snowflake

📊Business Analysis

🎯Target Audience

Our target audience includes online learners across various disciplines who seek personalized and engaging learning experiences. These are tech-savvy individuals with high expectations for interactive and responsive educational platforms.

⚠️Problem Statement

In the competitive landscape of online education, understanding and responding to learner engagement in real-time is critical. Traditional analytics fail to provide timely insights, resulting in missed opportunities to enhance course material and improve learner outcomes.

💰Payment Readiness

The online learning market is highly competitive, with providers willing to invest in advanced analytics to gain insights that drive student engagement and retention, thereby improving revenue and market position.

🚨Consequences

Failure to implement a real-time analytics solution could result in lost revenue due to decreased learner satisfaction and engagement, subsequently leading to higher dropout rates and a tarnished brand reputation.

🔍Market Alternatives

Some competitors utilize basic batch processing analytics, which deliver delayed insights. However, a real-time solution provides a significant edge by enabling immediate decision-making and content adjustments.

Unique Selling Proposition

Our platform's unique selling proposition is its integration of real-time analytics with machine learning to predict and enhance learner engagement dynamically, setting us apart from competitors who rely on slower, less responsive data processing methods.

📈Customer Acquisition Strategy

Our go-to-market strategy involves leveraging partnerships with educational institutions and online marketing campaigns to reach tech-savvy learners. By demonstrating our platform's efficacy through case studies and pilot programs, we aim to attract and retain a large user base.

Project Stats

Posted:July 21, 2025
Budget:$15,000 - $50,000
Timeline:8-12 weeks
Priority:Medium Priority
👁️Views:11563
💬Quotes:434

Interested in this project?