Business Context and Challenges
The customer operates a SaaS-based Smart Customer Relationship Management (SCRM) platform tailored for EdTech and online learning businesses. Their platform helps educational institutions, instructors, and content creators manage live course sales, student engagement, and real-time audience interactions through an integrated learning and broadcasting system.
A core component of the platform is live-streamed courses, where educators conduct interactive sessions to teach, engage students, and sell premium learning content. The success of these live sessions depends on real-time insights, enabling instructors to adjust course delivery, interact with students dynamically, and optimize sales strategies based on engagement trends.
However, the company faced several technical challenges in supporting these real-time needs:
1. Large-Scale Data with Uneven Distribution Across Users
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Large online learning platforms generated significantly more data than smaller educators, leading to performance imbalances.
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The top 10% of education providers accounted for most of the platform’s data, while smaller instructors had simpler usage patterns.
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Ensuring a seamless experience for all users, regardless of data scale, was a key challenge.
2. Need for Instant Student Engagement Analytics in Live Courses
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Instructors and moderators needed real-time insights into:
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Active student count and participation trends.
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Live chat interactions and sentiment analysis to track engagement.
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Course purchase and dropout rates to adjust pricing and content strategy dynamically.
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Data latency caused missed opportunities, as batch processing couldn't deliver live insights.
3. Scaling Challenges During Peak Course Sessions
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Spikes in student logins and interactions during live courses led to slow query performance.
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The system needed elastic scaling to handle surges in concurrent users without slowing down engagement analytics.
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Storage expansion was becoming difficult due to the growing volume of recorded lectures, student interactions, and chat logs.
Legacy Architecture and Technical Limitations
The company's original infrastructure used:
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Relational and NoSQL databases to store course sales and engagement data.
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Batch ETL pipelines to extract, transform, and load data into an analytical database for reporting.
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Caching layers to serve frequent queries faster.
Key Limitations of This Setup:
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Data Freshness Delays - Insights were delayed by several minutes to hours due to batch ETL pipelines.
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Inconsistent Performance - Live session analytics queries competed with other workloads, leading to unpredictable response times.
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Infrastructure Complexity - Managing separate databases for transactional, analytical, and AI workloads increased operational overhead.
Despite efforts to optimize queries and pre-aggregate reports, the platform struggled to deliver real-time insights, limiting instructors' ability to adjust teaching strategies and promotions dynamically.
Tacnode-Powered Solution: A Unified Real-Time Data Platform
The company replaced its fragmented architecture with Tacnode, unifying real-time analytics, transactional workloads, and AI-driven personalization in a single system.
Key Benefits of Tacnode for EdTech and Online Learning:
1. Instant Student Engagement Analytics for Live Learning Sessions
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Real-time insights on student activity, course purchases, and chat sentiment, allowing instructors to react instantly.
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Materialized views optimized analytical queries, improving data retrieval speed without adding query load.
2. AI-Powered Student Personalization and Real-Time Search
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Vector search enabled personalized course recommendations based on past student interactions.
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AI-driven student segmentation dynamically identified engagement levels, helping tailor content delivery.
3. Seamless Scalability for High-Concurrency Learning Sessions
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Tacnode's compute-storage separation ensured smooth performance, even during massive spikes in student logins and interactions.
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Automatic resource scaling allowed the system to handle thousands of concurrent students without affecting response times.
4. Simplified Infrastructure and Reduced Operational Overhead
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Eliminated batch ETL pipelines reducing data latency and system complexity.
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Unified transactional, analytical, and AI workloads, replacing multiple databases with a single, high-performance platform.
Business Impact and Future Growth
With Tacnode, the company transformed its live learning experience, ensuring that instructors,students, and content creators could access real-time engagement data without system lag.
By adopting Tacnode's real-time AI and analytics platform, the company achieved:
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A seamless learning and engagement experience, where instructors could interact with students dynamically.
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The ability to scale automatically during live courses, eliminating performance bottlenecks.
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AI-driven real-time personalization for students, improving content recommendations and participation.
Looking ahead, the company plans to expand AI-driven features, such as:
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Adaptive learning paths, where course difficulty adjusts based on student behavior.
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Automated instructor support, with real-time chat sentiment analysis to suggest engagement tactics.
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Dynamic pricing optimization, adjusting tuition based on student demand and interest levels.
Why Tacnode for EdTech?
Tacnode bridges the gap between real-time student engagement and AI-powered personalization, enabling EdTech platforms to deliver dynamic, interactive, and data-driven learning experiences at scale.