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Strategy-led migration to a modern data platform

For our customer, a Fortune 500 multinational healthcare company, we led a strategy-first engagement to plan the migration from multiple legacy data warehouses, including Teradata and other on-premises systems, to a unified, cloud-based data platform. Our advisory team helped the customer select the right future-proof data platform – Snowflake on AWS – based on their performance, compliance, and scalability needs. Together, we also designed a roadmap for using the platform’s evolving capabilities to power new data and AI initiatives, helping the organization adopt a scalable and innovative data foundation.

Technology stack

Signet of AWS

AWS

Signet of AWS S3

AWS S3

Signet of ANOW!

ANOW!

Signet of Snowflake

Snowflakes

Customer’s challenges

The migration initiative stemmed from architecture and performance limitations in the customer’s main Teradata environment. Poorly optimized data structures slowed data loading, limited resource allocations, and caused bottlenecks in delivering data to business stakeholders. Additionally, the lack of in-house skills for managing complex workloads and scattered legacy platforms created operational inefficiencies. The customer needed strategic guidance to select the right cloud solution and a long-term vision to evolve from a traditional data warehouse model to a modern, AI-ready data ecosystem.

Solution

We began the project with a comprehensive data strategy assessment, focusing on aligning technical goals with business priorities and data maturity. This included defining key evaluation criteria for platform selection, covering performance, governance, scalability, and AI-readiness.
Based on the strategy outcomes, the customer selected Snowflake on AWS, supported by a detailed migration and capability roadmap outlining current and future use cases. The implementation involved establishing Data Vault 2.0 as the enterprise modeling standard, deploying a Data Mesh operating model for domain-level autonomy, and building automation and orchestration processes using the ANOW! platform.

To ensure enterprise-grade security, we implemented end-to-end standards for identity management integrations (Active Directory, SAML/SSO, OAuth), RBAC frameworks with automated access provisioning, and data masking and security monitoring aligned with healthcare regulatory requirements.

Benefits

A clear strategic roadmap

guiding the evolution of the data platform toward advanced AI and analytics use cases.

Future-proof cloud data platform

selected and deployed, providing scalability, compliance, and operational efficiency.

Unified, standardized data modeling

(Data Vault 2.0) and automation reducing operational overhead.

Enhanced business autonomy

through a Data Mesh operating model.

End-to-end security controls

meeting the highest standards of the healthcare industry.

Faster, more reliable data delivery

and accelerated time to insights.

Expanded platform adoption,

growing from 800 to over 4,000 users and exceeding 1PB of managed data.

Significant reduction in administrative workload and ongoing costs,

enabling faster delivery of future migrations and initiatives.

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