Back to selected impact

Life sciences and regulated operations

Regulated Cloud Data & AI Trans-formation

Structuring an AWS-based target architecture and qualification approach for Data & AI and enterprise integration platforms.

AWSDatabricksGxPCloud Transformation

Context

A regulated organisation initiated a strategic move to establish its Data & AI platform in AWS, including Databricks and enterprise integration capabilities within a qualified cloud foundation.

Challenge

The transformation required coordinated decisions across the AWS landing zone, organisational account structure, identity, networking, security controls, Databricks workspaces, integration runtimes, qualification scope, evidence and operating responsibilities.

Mandate

Develop the target architecture and integrated workstream approach needed to move from a high-level mandate to a secure, qualified and executable platform programme.

Approach

  1. 01

    Structured the AWS organisation and account model around security, infrastructure and regulated platform domains.

  2. 02

    Defined platform boundaries and dependencies between the landing zone, Databricks and enterprise integration services.

  3. 03

    Separated platform qualification responsibilities from use-case validation responsibilities.

  4. 04

    Mapped identity, networking, logging, encryption, backup, evidence and change-control requirements into the target design.

  5. 05

    Created integrated planning for architecture, build, qualification, operational readiness and migration.

Capabilities established

  • AWS organisation and landing-zone target model
  • Databricks-on-AWS architecture
  • Enterprise integration runtime architecture
  • GxP scope and qualification boundaries
  • Integrated security, compliance and delivery workstreams

Impact

  • Converted a broad cloud mandate into explicit architecture decisions and workstreams.
  • Clarified dependencies between platform engineering, security, compliance and application delivery.
  • Created a basis for qualification evidence and production readiness from the beginning of the programme.
  • Reduced the risk of building a technically functional platform that could not be approved or operated sustainably.
Transferable lesson

In a regulated cloud programme, qualification cannot be added after the architecture is built. The control model, evidence flow and operational responsibilities must shape the target architecture from the outset.

Next case study

Enterprise Data & AI Platform Foundation

View case study

Contact

Discuss your Data & AI transformation priorities

For advisory inquiries, executive leadership opportunities or professional partnerships, please get in touch.

Contact Paul