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Building data foundation through strategy-first approach

For our customer, a Swiss-based private equity holding company, we supported the development of a data & AI strategy that defined a clear roadmap toward a modern cloud data platform. By first advising on how to prioritize data platform requirements based on business goals and data maturity, we ensured that every investment aligned with strategic objectives. Building on this foundation, we guided the customer in selecting the right platform, which led to implementing Snowflake on AWS as the core of their new, secure, and scalable data ecosystem.

Technology stack

Signet of AWS

AWS

Signet of AWS S3

AWS S3

Signet of Lambda

AWS
Lambda

Signet of Gitlab

GitLab

Signet of Terraform

Terraform

Signet of Docker

Docker

Logo of Datavault Builder

Datavault
Builder

Signet of Pentaho

Pentaho

Signet of Snowflake

Snowflakes

Customer’s challenges

The customer struggled with fragmented data practices and unclear priorities for platform modernization. Their legacy on-premises solution limited visibility and control over data access, putting sensitive information at risk. The lack of data governance, modeling standards, and developer collaboration further hindered innovation and slowed data-driven decision-making. The customer needed strategic guidance to define what to build first, and how to align technology choices with their organization’s data maturity and growth ambitions.

Solution

We initiated the engagement with a strategic assessment of data capabilities and business needs, conducting workshops with stakeholders to identify key value areas and prioritize requirements. This enabled the customer to move forward with clarity and direction.

Based on our recommendations, the customer adopted Snowflake on AWS as the foundation for their new platform. We established architectural and governance standards, implemented a Role-Based Access Control (RBAC) Framework to manage permissions efficiently, and introduced Data Vault 2.0 as the unified data modeling approach. This combination ensured both strategic alignment and operational excellence throughout the transformation journey.

Benefits

A data platform architecture

fully aligned with business strategy and maturity level, supporting sustainable data growth.

A secure and scalable Snowflake environment

designed to protect sensitive data and streamline scalability.

Implementation of a configurable RBAC Framework,

bringing effective and automated oversight of data access.

Established data modeling and security standards,

documented in an end-to-end governance playbook.

Faster, insight-driven decision-making

for portfolio management and investment operations.

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