How a top global logistics leader boosted BI performance by 65% with Snowflake

One wrong move during their Snowflake migration could have brought down hundreds of BI applications and reports. With legacy systems built over 15 years and rising maintenance costs putting operations at risk, this top-5 global logistics company faced its most critical data challenge yet.

Our experts at Snowstack stepped in to navigate this complex transformation. The outcome? A smooth migration that turned the company’s greatest risk into a long-term competitive advantage.

Key outcomes:

• Report performance improved by 65%, with dashboards running in minutes instead of hours.
• Infrastructure costs fell by 40% while system performance increased.
• The migration achieved zero disruption, maintaining 100% uptime.
• Over 65% of legacy SQL was converted automatically, saving months of effort.
• More than 40 developers were trained and upskilled on Snowflake.

‍Over the years, our BI teams developed an effective approach to data modeling, which had long been a strength. However, with the ongoing migration of the central data warehouse to Snowflake, we knew that adopting new tools could take months, if not years. We urgently needed support from Snowflake professionals to guide the adoption process and help our BI teams incorporate the new technology into their workflows.                                                           - Lead Data Architect


Client overview

The client operates as one of the top 5 key players in the industry, managing supply chains that span multiple continents and serve millions of customers worldwide. Their data ecosystem had evolved organically, supporting hundreds of BI applications that power everything from real-time shipment tracking to route optimization algorithms.

The client’s BI reports weren't just internal dashboard. They powered customer-facing systems that enterprise clients used to track shipments worth millions of dollars. Any disruption to these systems could trigger contract penalties and damage relationships with major accounts.

The challenge

15 years of business growth had created a BI environment that was difficult to manage. Hundreds of reports were built independently by different teams with varying skill levels. Although they all drew from the same data warehouse, each team applied its own transformation logic within separate BI systems. What began as team-specific solutions had grown into a web of technical debt that no one fully understood.

Our solution

Recognizing the critical need for modernization, the client made the strategic decision to unify their data model and move it to Snowflake alongside their ongoing data warehouse migration. We guided the client through five steps.

Step 1: identifying the foundation

Together with the client, we analysed their extensive BI landscape to identify the datasets most frequently used across reports. This joint assessment defined a minimum viable product (MVP) scope that would deliver immediate value and build momentum for the broader transformation.

Step 2: building the Snowflake environment

We worked with the client to establish a dedicated Snowflake environment designed specifically for BI collaboration. Together, we implemented:

• Standardized schemas and roles to ensure consistent data access patterns across teams
• Compute scaling strategies optimized for BI workloads
• Role-based access control (RBAC) to strengthen governance
• BI-specific access patterns tailored to Snowflake datasets

Step 3: automating the migration process

To accelerate the transition and protect prior investments, we partnered with the client to implement automated migration scripts that converted legacy SQL into Snowflake SQL. This achieved a 65% automatic refactor success rate, dramatically reducing manual work while preserving business logic.

Step 4: orchestrating seamless integration

In close collaboration, we designed and deployed new orchestration pipelines that synchronized Snowflake model builds with BI report refreshes. These pipelines were integrated with the client’s existing technology stack, including:

• Airflow Snowflake Operator for workflow management
• AWS SNS for notifications
• AWS S3 for data staging
• Git for version control

Step 5: investing in the team

Recognizing that technology transformation must go hand-in-hand with people transformation, we partnered with the client to deliver training for more than 40 BI developers. This knowledge transfer ensured teams could confidently work with Snowflake as their new backend, embedding long-term value into the organization.

Foundation for Future Innovation

Still running hundreds of disconnected BI reports with inconsistent data models?

Upgrading your BI architecture is no longer a matter of if. The real question is how quickly you can create a one source of truth before competitors pull so far ahead you can’t catch up. The companies winning today are those replacing broken reporting with accurate, unified data that every team can trust. Each month you delay, they improve decision accuracy and grow their market share.

We help you close that gap fast. Our Snowflake-certified experts bring years of experience and a proven approach to modern BI transformation. We can take years of messy, disconnected systems and turn them into a single, reliable analytics platform in months. With one source of truth in place, your teams spend less time fixing reports, more time acting on accurate information, and deliver faster business decisions.

Ready to unify your BI architecture on Snowflake?

Book your strategy session

Project details:

• Industry: Global Logistics & Supply Chain
• Duration: 3 months implementation
• Engagement Model: Migration service with comprehensive training & support
• Team Composition: Lead Architect, Data Engineers, Migration Specialists, BI Developers
• Frequently Used Snowflake Components: Warehouses, RBAC, Snowpipe, Tasks & Streams, Secure Data Sharing, Materialized Views, Time Travel, Stored Procedures
• Other Tools Integrated: Airflow Snowflake Operator, AWS SNS, AWS S3, dbt, Fivetran, Power BI, Azure AD

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