Our enterprise-grade big data analytics platform allows large regulators and governments immediate access to powerful data science capabilities that can integrate with their existing data sources.
The platform enables cross-sectional and longitudinal insights, prediction of outcomes and prescription of actions - allowing for better management, delivery and outcomes; and in the case of governments, evidence-based policy interventions.
Universal data “adaptor” that can plug into 200+ existing data systems and collect data, on a real-time and batch basis.
Allowing schools, colleges and governments the ability to collect data from disparate sources for holistic analytics and insights, hence, eliminating data silos.
Using advanced clustering and anomaly detection algorithms, quality issues are identified, providing a regular, non-tech savvy user with the control to know where the errors are happening and how to fix them
Instant data validations on the front-end to enhance data quality with pre-built data pipelines to automate data ingestion.
Leverages Apache Spark to achieve higher data processing speeds of about 100x faster in memory and 10x faster on the disk.
Capability to deploy machine learning algorithms to predict key students’ outcomes including attainment, progression and retention, and to identify key drivers behind them.
A self-service business intelligence layer that can be used by non-tech savvy users to query data, conduct drill downs, perform what-if analyses, and conduct deep dives ‘on-the-fly’.
They can also build their own dashboards and reports. Users don’t need to rely on the MIS/IT departments even for complex asks
User-friendly interface built upon Google’s material design principles, that has been extensively tested with end users, to maximise adoption and usage of insights that are generated by the platform
Cyber security tools and applications are built-in to provide encryption, multi-factor authentication and gateway firewalls to protect user data
Designed to ensure rapid end-to-end deployment and implementation across data collection, processing and insight generation
Data collected on over 100k students performance, behaviour and teacher efficacy was not being used. Our platform was setup to automate data collection, processing, and analysis to share insights with educators, real-time - including identification of students at-risk in terms of academic performance, behavioural issues, and school exits.
Data-driven approach to Education to Employment Transformation was enabled by collecting 800m+ data points across the journey from K-12 to Higher Education to Employment. Advanced machine learning algorithms were built and deployed to identify 10+ predictors of academic and career success, with simulations to estimate impact of policy interventions.