At a glance
Citizen data for the service was not easily assessable, useable, or trusted both inside the department and by other government departments. Significant data quality issues existed, and a rapidly changing data model was causing a large degree of wasted effort and broken reports downstream. Credera conducted a three week review of an existing on-premise data platform, leading to the creation of a remediation plan which we then helped to implement.
Inefficient, unscalable and end-of-life analytics platform.
Citizen data for the service was not easily assessable, useable, or trusted both inside the department and by other government departments. Significant data quality issues existed, and a rapidly changing data model was causing a large degree of wasted effort and broken reports downstream. The team and wider department did not have the required expertise to build a cutting edge cloud solution or to get it approved at architecture governance forums.
Architecture review, sign-off, build, and migration.
Credera conducted a rapid architecture review of the existing on-premise platform, recommending and implementing recommendations to shore it up whilst a new platform was built.
We began building a new Amazon Web Services (AWS) based platform, utilising serverless technology such as AWS Lambda and Amazon S3, Amazon EMR, and utilising government grade security and encryption tools. We provided a full implementation service including architecture, project management, engineering, data migration, test, and change management.
We embedded our resources within client teams to support their transition to Agile & DevOps culture and ensure that the hand-over was seamless.
Quality data available at a faster rate, supporting more rapid decision making and improving citizen experience.
The impact on UK citizens was increased efficiency and better service.
On the old platform, it took two days to process new data; now it only takes two hours.
This was critical during the COVID crisis to support accurate reporting and decision making, and ensured that resources were deployed to the areas most in need on a daily basis.
We ensured the report was available by 8am every day, including up-to-date data from midnight the previous night. We got great feedback from the teams using the new reports.
From a technical perspective, moving to the cloud has enabled data scientists to run analytics faster and enhance their data models with modern programming languages.
Our combined supplier/client team proved the power of cloud, and this now forms the basis for a data mesh architecture being rolled out across the department.