Home » Case Studies » Summit K12
2008 - Austin,TX
E- learning providers
51-200 employees
Overview
Summit K12, a US-based academic institution partnered with Folio3 to facilitate development of a digital solution to revolutionize its data processing capabilities, and scale exponentially through a data-driven approach. This problem was addressed by implementing an advanced Big Data Analytics platform, leveraging Cloud infrastructure for seamless scalability and cost-effective operations.
The Challenge
Processing Massive Data Volumes
Traditional data processing methods reached their limits as Summit K12’s data volumes grew exponentially, necessitating a shift to a more scalable solution.
The existing infrastructure struggled to cope with the ever-increasing demands of processing and analyzing vast amounts of heterogeneous data.
Embracing a CI/CD culture across the implementation teams to streamline and automate deployments while ensuring minimal downtime.
The Solution - Real-Time Big Data Processing & Analytics
Folio3 conducted a comprehensive assessment of Summit K12's infrastructure to identify modernization opportunities. Based on this analysis, a scalable, cloud-based architecture was designed to support real-time big data processing, efficient ETL processes, and robust analytics capabilities. The enhanced solution also included intuitive dashboards and real-time reports with interactive filters, significantly improving Summit K12’s ability to analyze data from multiple perspectives. Report generation times were reduced from minutes to milliseconds, empowering the client with responsive, data-driven insights for educational improvement.
Amazon Elastic MapReduce (EMR)
The solution leveraged Amazon EMR to process extensive datasets, providing the agility and scalability needed to manage Summit K12's growing data volumes without performance bottlenecks.
Real-Time Data Processing with Apache Spark
Provided fast, in-memory data processing for efficient analytics, enhancing computational speed and resource optimization.
AWS Glue for Automated Data Integration
AWS Glue was implemented to automate data discovery, cataloging, and transformation, simplifying ETL operations and ensuring seamless data integration.
Apache Iceberg for Large-Scale Dataset Management
Apache Iceberg supported the efficient management of Summit K12's educational datasets, enabling streamlined querying and data evolution tracking in the data lake.
CI/CD Integration for Seamless Deployment
Jenkins was integrated to automate testing and deployment, supporting a continuous integration/continuous deployment (CI/CD) pipeline that accelerated Summit K12's release cycles.
AWS Database Migration Service
Simplified the migration of existing databases to AWS with minimal disruption, ensuring data integrity and continuity throughout the transition.
Amazon Kinesis for Real-Time Data Streaming
Enabled real-time ingestion and streaming of educational data, allowing Summit K12 to derive dynamic insights from live data for immediate decision-making.
Infrastructure Automation with AWS CloudFormation
AWS CloudFormation was employed to manage infrastructure as code (IaC), enabling consistent and reproducible deployments, while reducing operational overhead.
Amazon Redshift for High-Performance Data Warehousing
To handle data-heavy queries, Amazon Redshift was used, providing a scalable and cost-effective data warehousing solution tailored for education analytics.
Technologies Used
Docker
Apache Spark
Apache Iceberg
AWS RedShift
AWS EC2-Autoscaling
Amazon Glue
Amazon ECS
Amazon RDS
Amazon S3
AWS Lambda
AWS CodePipeline
Moodle
PHP
ASP.net
React Native
Results & Achievements
Processing Terabytes of Data Daily
Folio3's robust infrastructure management facilitated the processing of millions of records of data on a daily basis.
10+ 3rd Party
Integrations
Summit K12 achieved integration with numerous external data sources such as, enhancing its analytics capabilities.
Significant Cost Savings
Substantial cost savings 30% for Summit K12 through efficient infrastructure design, optimizing their operational expenses while scaling their analytics capabilities.