Case Study:
International manufacturing company

Expert Thinking engineers Azure Data Platform for major retailer in collaboration with Softcat and Cognizant.

Requirements

The customer had engineered a basic Azure platform but engaged Expert Thinking as it lacked knowledge and key specific capabilities around cloud data platform engineering and DevOps best practices. The engagement therefore focused on the following requirements:

  • Work with the customer, Cognizant and Softcat to focus on the design and engineering of the cloud data platform.
  • Extend the existing Azure cloud environment to enable the cloud data platform to meet best practices relating to policy (security, regulation, performance etc)
  • Deliver the platform using DevOps best practices, working with the customer to upskill them to enable on-going support
  • Support the deployment of application code into test and production for the cloud data platforms

Critical success factors:

Partnership

Work closely with the other partners to deliver an end to end solution to meet the company goals.

Platform Quality

Ensure the platform is secure, scalable, performant and extensible.

Engineering Capability

Provide additional specialist resource to enable the platform to be engineered to aggressive timescales.

Our solution

We built a combined team comprising experts from Expert Thinking, Softcat, Cognizant and the customer to span the engagement, working across multiple time zones, with the following responsbilities:

  • Microsoft Azure cloud data platform and DevOps expertise to build the core platform components – Expert Thinking.
  • Application and base platform architecture and design – customer and Cognizant

On-going support – Softcat and customer.
Expert Thinking in particular focused on:

  • Validating the Azure Data Platform design in alignment with the other partners, focusing on security, compliance, performance, scale, redundancy, availability and connectivity.
  • Based on the Cognizant application solution design codified the environment using Infrastructure-as-Code (IaC) and Azure DevOps for pipeline-based deployment (aligning platform with application).
  • Engineered and deployed to both non-production (development, test, staging) and production environments an optimised, secure and cost efficient platform build.
  • Additional expertise to help the customer realise efficiencies in their Azure platform, allowing them to free up their resource to focus on new initiatives.

The benefits

We provided the successful delivery of a cutting-edge Azure data platform, meticulously constructed and maintained through code and automated pipelines. This platform played a pivotal role in supporting the expansion and monetisation of data across our customer’s business.

Additionally, our ongoing architectural oversight has been instrumental in guiding new projects to align with best practices and operational efficiency. The expertise of our engineers significantly reduced the workload on the customer’s in-house IT team, facilitating a shorter time-to-market for the solution. Notably, our team brought specialised DevOps and Infrastructure as Code (IaC) skills, along with advanced methods and tooling for cloud data platforms and Azure DevOps pipeline engineering—capabilities not previously available within the customer team or Cognizant.

Finally, we implemented optimisation strategies for unused assets, resulting in lower ongoing expenses and securing future discounts on provision.

Highlights:

Efficiency

Reduction in the amount of time internal teams spend on BAU activities.

Time to Market

We were able to work in complex organisational environment but still deliver complex platform engineering requirements to aggressive timelines.

Skills

Provide specialist capabilities around DevOps and IaC that were not available internally.

As with any complex project, there were some bumps along the way, but the approach to overcome these was testament to the partnership depth and expertise of the combined team

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