Get to know the cloud-first data warehouse on our joint free breakfast event on March 3 2020 in Brussels (Belgium).
Department of education
AT A GLANCE
We partnered with the Flemish Government’s Department of Education to build end-to-end data analytics applications in the hybrid cloud.
The results? Student grants can be paid out over 80% faster thanks to faster data processing, enablement of tens of new data citizens and the installment of new development standards.
ABOUT THE CUSTOMER
The Department for Education and Training is part of the Ministry of Education and Training for the Flemish community in Belgium.
The Department of Education and Training supports the minister in their role in managing, monitoring and evaluating Flemish education.
ABOUT THE CASE
One of the responsibilities of this body of governance is the assignment of student grants.
To improve theservice towards the public, the institution wants to increase the throughput speed of the request process. Hence, the governing team needs an automated solution to assign and report workload and process throughput metrics.
We built a solution based on a cloud data warehouse aimed at a fast time-to-value. One of the major focal points in this project was to safeguard data. Therefore, we designed a data analytics platform based on Amazon Web Services from the ground up.
Throughout all phases of the process, developments are based on architectural best practices, code-defined infrastructure and automated delivery pipelines.
DESIGNED FOR BUSINESS CONTINUITY
By implementing AWS’ Well Architected Framework we have been able to deliver a pragmatic solution that combines opimal time-to-market with fail-safe daily operations
The new architecture not only allows the department of Education’s team to operate in a state-of-the-art, automated, cost effective and reliable environment that follows best practices and uses the newest and most productive technologies.
They need to spend less time on ordinary management tasks and focus on addressing the governments rapidly changing business demands.
Upon project delivery, the internal data engineering team was self-reliant and could adapt the end-to-end pipelines without expert intervention required.