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Data products and AI foundation transformation
A consumer health company used governed Snowflake data products to support analytics, self-service and AI. Learn more in this case study.
1
The better the question
How do you scale self-service without sacrificing governance and trust?
How we built a governed Snowflake data foundation supporting analytics, self-service and AI.
Snowflake capabilities
|
Cortex Agents |
Cortex Analyst |
Cortex Search |
Semantic Views |
|---|---|---|---|
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Dynamic Tables |
Database Roles and Managed Access |
Cortex Code (CoCo) |
Snowflake Intelligence (CoWork) |
Project highlights
- Built a governed Snowflake data foundation supporting self-service analytics and AI.
- Created 12 certified data products across five business domains.
- Reduced expected requests to the central data team by more than 50%.
- Enabled more than $5 million in projected business value across seven priority data and AI use cases.
- Established a reusable operating model expected to reduce delivery effort for future initiatives by around 40%.
- Ongoing client engagement.
About the client
The client is a leading consumer health organisation operating in 13 markets across Asia-Pacific.
It has ambitious plans to accelerate growth through better use of data and AI, while operating within a highly regulated environment that demands strong governance, trust and accountability.
Although valuable data existed across commercial, supply chain, finance and regulatory functions, teams struggled to find, trust and reuse it quickly enough to support decision-making in the flow of commercial work.
Client request
The client needed more than a Snowflake implementation partner. They needed a team that understood both consumer products and enterprise data, capable of translating business priorities into governed data products that could be reused across analytics, self-service and AI.
Challenge
The organisation needed more than a new data platform. It needed a way to make trusted data reusable across the business without creating another layer of reports, dashboards and manual processes.
The solution had to solve three connected challenges:
- Turn complex business priorities into reusable, domain-owned data products that could support multiple business functions and future AI use cases.
- Make trusted data easy to discover, request and reuse through a governed internal marketplace, reducing duplication and inconsistent reporting.
- Enable business users to ask questions in natural language and receive trusted answers without relying on the central data team or waiting for new reports to be built.
2
The better the answer
Govern once, then reuse trusted data everywhere
A regulated consumer health organisation needed trusted, reusable data to support growth, decisions and future AI.
Approach
We started with the business, not the technology.
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01 |
Define the value |
Align business leaders around the highest-value decisions and prioritise 59 opportunities into a focused transformation roadmap. |
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Database Roles and Managed Access |
Established clear ownership, governance, funding and decision rights so data products become managed business assets. |
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Prove the approach |
Delivered lighthouse use cases focused on pricing, automation and commercial decision-making that demonstrated business value, reduced implementation risk and validated the reusable data product model before scaling further. |
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Build the foundation |
Implemented a Snowflake-powered data product backbone with certified data products, semantic models and marketplace discovery to create a trusted enterprise data foundation. |
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Drive business adoption |
Supported business teams through change management, data literacy and adoption activities so trusted self-service became part of day-to-day decision making. |
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Scale through reuse |
Expanded the catalogue of certified data products across new domains, enabling future analytics and AI use cases to be delivered faster through reuse rather than rebuilding. |
Solution
Govern once. Discover, trust and use everywhere
Rather than creating another reporting layer, we helped the client establish a governed operating model where data is certified once, managed centrally and reused across analytics, reporting, automation and AI.
Productise business data
We transformed high-value operational data, including product performance, sales, inventory, supply chain, finance, regulatory and customer information, into certified, domain-owned data products. Each product included agreed business definitions, ownership, quality rules and access controls so every team could work from the same trusted information.
Make trusted data easy to discover
Instead of searching across multiple reports or requesting new data extracts, business users can discover, request and reuse certified data products through an internal marketplace. This removes duplication while ensuring everyone works from the same governed foundation.
Put trusted insights directly into business users' hands
Using Snowflake Intelligence and semantic models, business users can ask questions in plain English and receive answers based on governed business data without writing SQL or waiting for the central data team.
For example, commercial teams can:
- Identify the highest-performing or underperforming product SKUs across individual markets.
- Compare pricing and discount performance between regions.
- Analyse customer, distributor or channel performance.
- Investigate supply and demand trends before they become operational issues.
- Generate charts and presentation-ready insights in seconds rather than waiting days for a reporting request.
Because every answer comes from certified data products and shared business definitions, teams spend less time debating which report is correct and more time acting on trusted insights.
Create a reusable foundation for AI.
The same governed data products now power analytics, automation and future AI use cases. New solutions can be developed without rebuilding pipelines or redefining business rules, allowing innovation to scale while maintaining consistent governance, security and trust.
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The better the world works
Delivering measurable value through trusted data products
Clear governance, shared definitions and reusable data products help drive business outcomes and future innovation.
Results
The project changed how the organisation works with data by giving business teams direct access to trusted, reusable information.
- More than $5 million in projected value across seven priority business initiatives over three years from reusable data products.
- 12 certified data products developed or under development.
- More than 50% reduction in expected requests to the central data team as business users gain the ability to answer their own commercial questions.
- Around 40% lower effort and cost than comparable programmes through accelerators and repeatable data product patterns.
- More than $2 million in additional projected value as other business functions reuse the same foundation.
- Five priority business domains connected through a single governed data products operating model.
Lessons learned
Most organisations do not struggle because they lack data; rather, they face challenges when different teams define and measure the same business metrics differently.
Agreeing once on business definitions, ownership and governance creates a trusted foundation that can be reused across the enterprise.
The project reinforced a key insight: the greatest value from AI comes when it is built on trusted, governed data. When governance is designed into the foundation, it accelerates adoption and empowers teams to innovate with confidence.