Learn from our clients’ successes

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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$800K in cloud costs every month, and no explanation. For a leading financial services firm, cloud was critical to scaling the business, yet it had become one of the fastest-growing expenses. Monthly spend had passed $800K with no clear breakdown of where the money was going. By partnering with us, they gained full visibility and, within 90 days, turned uncontrolled costs into a governed, AI-ready platform built for scale.

Key outcomes:

• Data ingestion latency reduced by 80%
• AI-readiness achieved in 90 days
• Real-time cost monitoring and automated optimization
• Modern data platform for analytics, ML, and AI use cases

Client overview

Our client is a financial services company generating $500M in annual revenue with a team of 2,500 employees across North America and Europe. In the midst of rapid growth, they were transitioning from legacy systems to a modern cloud data platform built on Snowflake. But they faced rising cloud costs and a fragmented data landscape.

The challenge

Our client had ambitious AI and GenAI goals, but lacked the foundational architecture to support them cost-effectively.

The client knew what Snowflake could deliver but needed the right partner to design, implement, and operationalize a solution that would translate that capability into measurable business value.

Our solution

The client set out to gain full visibility, governance, and scalability in their cloud environment. By partnering with us, they implemented a modern, AI-ready data platform built on Snowflake to address the challenges limiting performance.

Unified data Ingestion with OpenFlow

They consolidated structured and unstructured data from SharePoint, Salesforce, and custom systems into a single ingestion framework, eliminating fragmented pipelines and enabling real-time analytics.

Centralized Metadata and governance with Horizon Catalog

They integrated metadata from BI tools, dbt models, and Iceberg tables into one governed repository, achieving full lineage visibility, consistent KPIs, and stronger compliance controls.

Consistent logic with semantic views

Business rules were embedded directly into the data layer. This made sure that every team worked from the same definitions for analytics and AI training.

Self-service analytics with Cortex AI SQL

Business users can now query governed datasets in natural language, reducing reliance on engineering and accelerating decision-making.

FinOps cost governance

Daily cost visibility, clear ownership tracking, and accurate forecasting were integrated into operations, turning cost control into a proactive practice.

Why it mattered

If you can’t see your cloud costs, you’re losing money. In many enterprises, unused services, duplicate workloads, and unclear cost ownership quietly drain millions each year. Without visibility and governance, budgets overspend, AI projects stall, and growth slows.

Our team provides the insight and control to stop waste, making every cloud dollar accountable and directly tied to business results. So start controlling your cloud spend today.

Book a Snowflake consultation.

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Project details:

• Industry: Financial Services
• Duration: 90 days (initial build) + ongoing support
• Engagement Model: FinOps & AI readiness program
• Team Composition: Snowflake Solution Architect, Data Engineers, BI Specialist, Data Governance Lead
• Frequently Used Snowflake Components: OpenFlow, Horizon Catalog, Cortex AI SQL, Semantic Views
• Other Tools Integrated: SharePoint, Salesforce, dbt, Fivetran, Power BI

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How do you compete in an AI-powered market when you're still running on spreadsheets? In the fast and tightly regulated pharmaceutical sector, compliance and speed to market are key competitive advantages. As the industry leaned into AI and cloud transformation, a $200M pharma distributor in the US found itself at a crossroads. To modernize their data stack, they turned to our team. And in just 90 days, we deliver a fully cloud-native Snowflake implementation.

Key outcomes:

• 80% reduction in reporting lead times across all business units
• Complete cloud migration from fragmented on-premises systems to a unified data platform
• Enterprise-grade governance with pharmaceutical compliance controls and auditable access
• AI-ready infrastructure with scalable foundation for advanced analytics and machine learning

Working with Snowstack was a game-changer. Their team came in with a clear methodology, deep Snowflake expertise, and zero handholding needed. We didn't have to move a muscle in-house - they brought it all, tailored it to our business, and delivered fast                                    — CTO


Client overview

Operating across the Southeastern United States, the client had built a solid $200M business serving healthcare providers with essential medications and medical supplies. The team relied entirely on fragmented, on-premises systems, including legacy ERP, CRM, and custom databases that had served them well for years but now created significant operational issues.

The challenge

As competitors adopted cloud analytics and AI to optimize inventory, refine pricing, and enhance customer operations, the performance gap was no longer something that could be overlooked.

The cost of waiting was becoming clear: decisions took longer, compliance became risky, and competitors with better data systems were pulling ahead.

Our solution

Instead of investing time and resources into building internal data teams from the ground up, the company engaged with our team to deliver a fully managed Snowflake implementation using our proven Summit Quest Framework (SQF).

• Discovery and audit

We started by conducting a deep audit of the client's legacy ERP, CRM, and inventory systems. This allowed them to surface integration gaps, data duplication issues, and performance issues.

• Snowflake implementation and migration

With the client, we deployed Snowflake as the central data platform and automated the ingestion of historical and operational data. Through our proprietary accelerators, we helped establish scalable data pipelines and standardized data models across domains.

• Managed data platform setup

With our architectural guidance, the client built a production-grade Snowflake environment tailored to their business needs. We implemented logical data models across finance, sales, and supply chain, integrated dedicated compute layers, and rolled out monitoring dashboards for performance, usage, and cost control.

• Governance and compliance enablement

To support data security and meet relevant compliance expectations, we implemented a practical governance framework. This included role-based access controls (RBAC), data lineage tracking, and fully auditable permissions. Our work ensured the client could confidently manage sensitive data, such as pricing and patient records, while enabling secure access across teams.

• AI readiness foundation

Positioning themselves for long-term innovation, the client used our support to define a clear AI roadmap. Together, we prioritized use cases such as predictive analytics and segmentation, curated trusted datasets, and built the architecture to support Snowflake-native AI and machine learning at scale.

Execution

We delivered the project with a structured approach that balanced steady progress and expert input. A dedicated team ensured clear communication, alignment, and steady progress across the full timeline. At key stages, we brought in specialists to address Snowflake optimization, governance, and AI architecture. This allowed us to resolve complex challenges without slowing the project and ensured the final solution was high-performing and ready to support advanced analytics.

From legacy systems to future-ready operations

Still making strategic decisions with fragmented systems and inconsistent KPIs?

This pharma distributor replaced outdated systems with a modern data foundation built for real-time insights, regulatory compliance, and AI-driven innovation. With our team as their strategic partner, they now operate much more efficiently across every function.

The companies that dominate their markets in the next 5 years will be those that turn data into competitive advantage today. The question is no longer whether you need a modern data infrastructure. It is whether you can build it fast enough to make an impact.

If your organization is still navigating disconnected systems, manual reporting, or limited data access, we can help you take the next step. Our team delivers more than implementation. Ready to see what's possible?

Book your strategy session

Project details:

• Industry: Pharmaceutical Distribution
• Duration: 3 months implementation
• Engagement Model: Full buildout + knowledge transfer
• Team Composition: Snowflake Solution Architect, Data Engineers, BI/Visualization Specialist, Project Manager, Governance Specialist
• Frequently Used Snowflake Components: Warehouses, RBAC, Snowpipe, Tasks & Streams, Secure Data Sharing, Materialized Views
• Other Tools Integrated: AWS, Python, dbt, Fivetran, Power BI, Excel, REST APIs, Active Directory

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What if your team could eliminate manual data tasks, accelerate insights, and build a scalable, future-proof data foundation? This was the challenge facing the European division of a global FMCG enterprise. Struggling with daily operational challenges, they partnered with our team. Together, in 3 months, we modernized their data infrastructure.

Key Outcomes:

• 98% less manual data work with over 30 automated ELT pipelines
• Dashboard load time dropped from 15 minutes to under 1 minute
• 80% faster access to insights across business functions
• Secure, role-based architecture deployed on Snowflake and AWS

‍What used to take us hours of manual cleanup across dozens of Excel files is now a seamless process. The Snowstack team didn't just give us technology - they gave us our time back. We now build better reports much faster, and can finally think about predictive analytics as a reality, not just a wish. They felt like part of our team from day one. 

                  — Head of Sales Intelligence


Client overview

Our client is a European division of one of the world's leading Fast-Moving Consumer Goods companies, operating in over 180 countries. With a local team of approximately 100 people, they oversee sales performance, financial planning, and analytics across a broad portfolio of consumer products and retail partnerships.

The challenge

Before working with Snowstack, the European team relied entirely on Microsoft Excel for managing critical business data. As data volumes grew, spreadsheets became unstable, requiring manual workarounds, such as splitting files and reprocessing data daily.

Analysts were losing up to 20 hours each week on repetitive data preparation tasks, delaying insights and exposing the organization to risks around accuracy, security, and compliance. Without automation or scalable architecture, the team couldn’t support advanced analytics or any progress toward AI readiness.

Our solution

We didn't just migrate their data. We built a modern, scalable data platform from the ground up

Phase 1: Strategic discovery and planning

• Conducted in-depth workshops with Sales Intelligence, Market Intelligence, and Financial Planning teams.
• Mapped 15+ fragmented data domains.
• Designed a governance framework that would meet both local needs and global compliance standards.

Phase 2: Snowflake architecture implementation

• Multi-warehouse setup on AWS with role-based access control segmented by department.
• Three-layer architecture (Staging → Integration → Presentation) optimized for efficient ELT pipelines and clean data handoffs.
• Enterprise-grade security built into the foundation, with RBAC aligned to multinational compliance standards including PII and GDPR.

Phase 3: Automated pipeline development

• 30+ orchestrated data pipelines fully replaced manual processing and human error.
• Migration of 10+ years of historical data spanning over 50 million rows across sales, marketing, and finance teams.
• Real-time integration development through automated delta ingestion from external APIs and MongoDB sources.
• Built-in data quality checks using pandas-based data validation.

Phase 4: Business intelligence transformation

• Rebuilt Power BI dashboards with direct Snowflake connections for faster, more reliable reporting.
• Trained more than 20 analysts and executives to use SQL in Snowflake Workbooks, boosting team capability.
• Introduced self-service analytics, so that business users could find answers without relying on IT teams.

The results

Migrating to Snowflake resulted in clear improvements across data workflows, reporting speed, and team productivity. Below, you can see the key performance metrics before and after the implementation.

Proven insights to keep you ahead

Still relying on manual reporting processes?

Without a scalable system, teams spend more time fixing data than using it. In the market where data volume is high but data literacy is uneven, this project shows what becomes possible when the right infrastructure is paired with the right strategic thinking.

Our experts didn’t just deliver new tools. We partnered with the client to redesign how their teams think, collaborate, and make decisions. Our team helps organizations move beyond outdated processes with a governed, AI-ready data infrastructure that scales with business demand.

Are you ready to grow? Talk to our experts.

Project details:

• Industry: Fast-Moving Consumer Goods (FMCG)
• Duration: 3 months (implementation)
• Engagement Model: Full buildout with training & support
• Team Composition: 1 Lead Data Engineer, collaborating with 3 business units
• Frequently Used Snowflake Components: Warehouses (XS–M), RBAC, Schema Design, Query History, Worksheets
• Other Tools Integrated: AWS, Python, ETL, Bash, Jupyter Notebooks, Power BI, MongoDB, REST APIs, WinSCP, Facebook Prophet

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Companies that fail to master their data platforms in 2025 will not just fall behind. They will become irrelevant as AI-native competitors rewrite the rules of the market. One global FMCG manufacturer recognized this early on. By partnering with us, they turned their underperforming Snowflake environment into an innovation engine.

Key outcomes:

• 30% reduction in Snowflake costs through intelligent optimization
• 60% faster incident resolution with 24/7 monitoring
• 5+ new AI/BI use cases unlocked from reliable, curated datasets
• 100% audit readiness for SOC 2 and GDPR frameworks

‍Having a dedicated Snowflake team that truly understands our platform made all the difference. We no longer chase incidents or firefight pipeline issues - we’re focused on enabling the business. Their ownership, responsiveness, and expertise elevated our data platform from a bottleneck to a strategic asset.                                               - Senior Director, Data Platforms


Client overview

The client is a multinational Fast-Moving Consumer Goods (FMCG) manufacturer operating in over 180 countries through both corporate offices and an extensive franchise network. With global revenues exceeding $45 billion and more than 6,300 employees worldwide, they manage a diverse product portfolio distributed through complex regional supply chains.

The challenge

Despite investing in modern cloud infrastructure, the client was stuck. Their internal teams lacked the specialized expertise needed to run the platform. When key engineers left, so did the expertise. This resulted in growing technical debt. Critical pipelines regularly failed or ran late. Compliance and audit demands became difficult to satisfy due to inconsistent governance. Without proper optimization, Snowflake costs increased. As a result, the platform’s reputation fell from being seen as an innovation enabler to becoming a business blocker.

What made things even harder was the seasonal nature of FMCG operations. Demand for data engineering resources fluctuated throughout the year. Resource needs spiked during busy times and dropped during slow periods. This led to ongoing hiring and retention challenges. Meanwhile, competitors kept moving forward with steady expertise and data strategies.

Our solution

The client wanted a better way to manage their data and prepare for future growth. They asked us to provide a full Snowflake delivery team that could handle the project from start to finish. Instead of hiring separate contractors, they gained a team of Snowflake-certified experts who worked together to deliver the solution quickly.

Our execution

With our support, the client regained platform stability, resolved recurring system issues, and accelerated the delivery of new data solutions. The Snowflake environment became easier to manage, more predictable, and better aligned with business priorities.

Structured collaboration

The client led a phased rollout, supported by bi-weekly service reviews and backlog planning sessions. We worked directly within their workflows (Slack, Teams, Jira) and joined daily stand-ups and steering meetings. To help address long-standing challenges with knowledge retention, we introduced clear RACI ownership and thorough documentation practices.

SLA-Driven Support Model

The engagement featured a service model tailored to the client’s operational needs. Platform support was aligned to business hours, extended hours, or 24/7 coverage depending on requirements. SLAs were defined by incident severity, with guaranteed response and resolution times in place. To give the client real-time visibility and control, we implemented automated monitoring and alerting.

Platform optimisation and future-proofing

The client was committed to building a Snowflake environment that could scale with the business. With our support, they focused on optimising performance, controlling costs, and staying ahead of future demands.

Faster delivery, greater impact

We supported ongoing initiatives by onboarding new data sources, integrating BI tools and APIs, and maintaining platform standards across internal and third-party teams. Automation and reusable pipelines cut source-to-Snowflake integration time from weeks to days.

Continuous improvement and strategic reporting

Monthly platform reports provided clear visibility into KPIs, usage trends, incidents, and optimisation opportunities. This helped the client move from reactive support to a proactive and data-driven platform management.

Governance and security practices

To support regulatory and internal compliance requirements, we implemented platform-wide governance controls. These included RBAC, data masking policies, access audits, and full alignment with SOC 2 and GDPR frameworks.

The results

Strategic value

Owning a data platform is not the goal. Making it work for the business is.

This partnership showed how Team as a Service can turn a complex platform into a strategic asset. By working directly inside the client’s operations, our certified Snowflake experts turned a complex, high-maintenance platform into a scalable foundation for growth.

Now, they are ready to take on AI and advanced analytics, backed by an architecture built to grow with the business.

At Snowstack, we don’t just help companies manage Snowflake. Our model helps enterprises stay ahead in a data environment that keeps changing

Ready to turn your Snowflake platform into a competitive advantage?

Let’s talk about how our team can help you get there

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Project details:

Industry: FMCG

Duration: Ongoing (Support Service)

Engagement Model: Team as a Service

Frequently Used Snowflake Components: Core Snowflake Data Cloud, Snowpipe, Tasks & Streams, Materialized Views, Secure Data Sharing, RBAC & Data Masking, Snowpark, Resource Monitors

Other Tools Integrated: dbt, Fivetran / Airbyte, Power BI / Tableau / Looker, Azure Blob / AWS S3 / GCP Storage, GitHub / GitLab, ServiceNow / Jira, Okta / Azure AD, Great Expectations / Monte Carlo

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