Manage millions of SKUs on one accurate, governed Snowflake platform

Escape spreadsheet chaos and fragmented systems. We build Snowflake platforms that handle millions of SKUs and sales records, with automated pipelines that cut manual prep from hours to minutes, so your global teams work from one accurate, governed source of truth and your AI agents answer correctly.

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What you gain

From spreadsheet chaos to one source of truth

If you run data in consumer goods, you are likely stitching together ERP, POS, e-commerce, and supply-chain data across regions, with critical numbers living in spreadsheets. We bring it all into Snowflake, automate the pipelines, and reconcile it into one governed source of truth, so SKU, sales, and margin data is accurate, fast to access, and ready for analytics and AI agents.

Free consultation
Features

Pipelines that stay reliable under load

Automated, monitored ingestion replaces fragile manual prep, so data lands on time and stays consistent across regions, even during peak demand and promotions.

One governed source of truth

We reconcile data from ERP, POS, and e-commerce into consistent, governed definitions, so global teams and AI agents all read the same accurate numbers instead of five conflicting versions.

Benefits

Why consumer goods leaders work with us

Scale without limits

Run large SKU and sales datasets on a platform that grows with your catalog, channels, and markets.

Hours of prep become minutes

Automated pipelines remove manual data wrangling, so your teams spend time on decisions, not spreadsheets.

One clear source of truth

Global users work from the same accurate, reconciled data instead of conflicting regional spreadsheets.

Costs you can see and control

Clear visibility and FinOps controls keep cloud spend predictable as your data volumes grow.

Transparent and proven methodology

Our signature Snowflake consulting methodology

Our signature transparent methodology, refined through years of Snowflake experience, coordinated to deliver fast, high-quality results.

Sucess stories

How our Snowflake consulting transforms data operations

Case study
5 min read

How a global finance leader achieved AI readiness in 90 days with Snowstack

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.

$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.

Challenge area Industry context Specific issues at client Business impact
Fragmented Infrastructure 80–90% of enterprise data is unstructured, yet only 18% of organizations report being able to take advantage of it. Data scattered across SharePoint, Salesforce, and custom tools with no unified architecture for AI initiatives. High maintenance overhead, inability to leverage enterprise-wide data for AI.
Unstructured Data Processing Managing unstructured data is challenging for 71% of enterprises. Struggling with the processing of unstructured data. Slow time-to-insight, missed opportunities for AI and advanced analytics.
Trust & Governance 62% of organizations cite lack of data governance as the top hurdle to AI initiatives. Dashboards showed conflicting KPIs due to inconsistent definitions and missing lineage tracking. Low confidence in analytics, compliance risks, and poor decision-making.
Scalability & Agility Legacy data architectures can’t support AI workloads or scale without high operational overhead. Manual processes, siloed datasets, and outdated architecture limited agility. Blocked innovation, delayed AI adoption, and competitive disadvantage.

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.

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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.

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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

Case study
5 min read

How a $45B FMCG leader regained control of their Snowflake platform with Snowstack

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.

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.

Role Responsibility
Service Delivery Manager Coordination, client communication, strategic alignment
Snowflake Platform Lead Solution architecture, technical strategy, governance
L1/L2 Support Specialists Incident response, monitoring 24/7, routine maintenance
L3 Dev Team Experts Complex integrations, enhancements, and advanced troubleshooting
Data Engineers Pipeline development, data modelling, ETL optimization (optional based on client needs)
DevOps/FinOps Specialists Infrastructure automation, cost optimization, performance tuning (optional based on client needs)
AI/BI Architects Advanced analytics, machine learning enablement, dashboard strategy (optional based on client needs)

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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

Area Before After
Platform Stability Recurring system issues, unpredictable performance. Stable Snowflake environment aligned with business priorities.
Collaboration External support created silos, unclear ownership, and poor knowledge retention. Embedded in client workflows, clear RACI ownership, and a strong documentation culture.
Support Model Reactive issue handling, manual oversight, and inconsistent coverage. SLA-driven with defined severity levels, automated monitoring, and 60% faster resolution.
Cost & Performance Not optimised Snowflake’s cost with limited scalability planning. Up to 30% cost reduction with no performance loss, scalable architecture.
Delivery Speed Weeks to integrate new data sources, limited AI/BI enablement. 5+ new AI and BI use cases supported by production-ready datasets.
Reporting & Visibility Limited insight into platform health and usage trends. Monthly KPI-driven reports, proactive platform optimisation.
Governance & Security Gaps in compliance and audit readiness. Full SOC 2 and GDPR alignment, 100% audit readiness with traceability.

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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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From 80% faster reporting to 65% cost savings, here's how our clients turned data into business results.

View all stories

Enterprise-grade security

Enterprise security controls and governance frameworks built into every Snowflake implementation. Role-based access, data encryption, and audit trails configured from day one.

SOC 2 TYPE II
Certified

HIPAA Certified

Testimonials

What our clients say

What used to take us hours of manual clean-up 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

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

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, Regional Pharma Distributor

Over the years, our BI teams developed an effective approach to data modelling, 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

FAQs

Answers to common questions about building scalable, governed Snowflake platforms for consumer goods.

Free consultation
Can Snowflake handle millions of SKUs and our sales data without slowing down?

Yes. Snowflake separates storage from compute and scales automatically, so we can design architecture that handles millions of SKUs and high-volume sales data while keeping reporting fast. As your catalog, channels, and markets grow, the platform grows with them, with no manual re-architecting every time volumes jump.

We run our business on spreadsheets and disconnected systems. How do you fix that?

We bring ERP, POS, e-commerce, and supply-chain data into one governed Snowflake platform and automate the pipelines that used to be manual. Reconciled, consistent definitions replace conflicting spreadsheets, so your global teams work from one accurate source of truth instead of five versions of the number.

How do you make sure global teams are all working from the same numbers?

We reconcile data source-to-report and define each metric once in a governed semantic layer, so a SKU, a sales figure, or a margin means the same thing in every region. Dashboards and AI agents read that same logic, which is what turns five regional versions of the truth into one.

Will automating our pipelines actually save time, or just move the work?

It removes the work. Automated, monitored ingestion replaces manual prep and reconciliation, cutting routine data wrangling from hours to minutes and catching broken or partial feeds before they reach a report. Your teams spend their time on decisions, not on stitching spreadsheets together.

How do we keep cloud costs under control as our data grows?

We build FinOps in from the start: warehouse right-sizing, auto-suspend, and usage monitoring, so spend stays visible and predictable even as volumes climb. You get clear control of cloud costs instead of bill shock at the end of the quarter.

How fast can we see results in consumer goods, and how do you price it?

We start with a fixed-scope assessment that maps where your SKU and sales data is fragmented and the fastest path to one platform. Most clients see early wins on data quality and reporting speed inside the first 30 days. Pricing is transparent: a fixed-fee assessment first, then scoped sprints or a fractional platform team.

Still have questions?
Free consultation

Ready to put your SKU and sales data on one platform?

Book a free consultation with a senior Snowflake architect and we will map where your consumer goods data is fragmented and the fastest path to one accurate, governed source of truth.

Free consultation