Releasing real-time data for a large government department

Credera leveraged world-class expertise in big data to drive improved citizen experience via near real-time data integrations for the UK government.

At a Glance

Credera conducted a three-week review of an existing on-premises data platform that ultimately reduced a two-day process to two hours. We helped to create and implement a remediation plan that addressed concerns with the accessibility, usability, and trustworthiness of citizen data.

The Challenge

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 caused 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 get it approved at architecture governance forums.

The Solution

Architecture review, sign-off, build, and migration.

Credera conducted a rapid architecture review of the existing on-premises platform, making recommendations and implementing those changes to shore it up while a new platform was built.

We began building a new Amazon Web Services (AWS)-based platform, utilizing native serverless technology including government grade encryption. We provided a full implementation service including architecture, project management, engineering, testing, and change management.

We embedded our resources within client teams to support their transition to agile and DevOps culture and ensure a seamless handover.

The Results

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-19 crisis to support accurate reporting and decision-making, and ensure resources were deployed to the areas most in need on a daily basis.

We ensured the report was available by 8 a.m. 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 the cloud, and this now forms the basis for a data mesh architecture being rolled out across the department.

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