Snowflake Modernization
Outcomes

Off Legacy.On Snowflake.Ready for Innovation.

Legacy warehouses are slow, costly, and hard to govern. Hakkoda and IBM migrate enterprises onto Snowflake at pace, with AI-accelerated tooling, then build the analytics, governance, and data products that run on top. These are production results.

Before
Enterprise data science was boxed in by an aging Oracle Exadata platform, with mounting legacy tech debt slowing analytics and raising cost.
US Foods · Supply Chain
→
After
Hakkoda migrated to a Snowflake and Amazon Web Services stack, standardized ingestion and transformation, retired Exadata, and unlocked DataOps across the business.
$10M EBITDA · 1000x faster reporting
Before
Federal healthcare data sat on legacy infrastructure, driving high operating cost and slow query performance across more than two petabytes.
CMS · Government
→
After
Hakkoda modernized the estate onto Snowflake, validating more than two petabytes of data and re-platforming for governed, high-performance access at federal scale.
60% lower cost · 85% faster queries
Before
Slow, manual data pipelines delayed analytics for a global medical technology leader, holding back time to insight.
Edwards Lifesciences · Healthcare
→
After
Hakkoda re-engineered the pipeline estate on Snowflake, collapsing run times to minutes and lifting data processing efficiency across the board.
97% data efficiency · 5-min pipelines

A modernization built on your data, your workloads, and your governance posture. AI-accelerated migration moves you at pace, then analytics, machine learning, and native apps run on one governed platform. Built and operated on Snowflake, with Hakkoda accelerators and IBM.

© IBM Corporation 2026. All rights reserved.
Systems

The foundation for innovation.

A real Snowflake move is not a lift and shift of legacy code. Pipelines are rationalized, models are rebuilt for the platform, and governance is designed in. Each migration is tailored to how the business actually runs on its data.

Example Snowflake Architectures →
Not a lift and shift
A true modernization
Legacy code and models are rationalized and rebuilt for Snowflake, not copied over. You move the business forward, not sideways onto the same problems.
Not a multi-year project
Migration at pace
AI-accelerated tooling and Hakkoda accelerators compress the timeline, with migrations delivered up to 10x faster than traditional methods.
Not just a warehouse
A platform to build on
Snowflake becomes the foundation for governed analytics, machine learning, and native data applications, not only cheaper storage.
Not the finish line
New revenue and reach
Native apps and data products turn the platform into new markets, new customers, and new revenue, long after the migration is done.
"Hakkoda's unique delivery model and deep expertise in data engineering allowed us to get value from the relationship in a matter of days. They're helping us use Snowflake in the way it was intended."
Chuck Sample, VP of Analytics and Data Science, US Foods
© IBM Corporation 2026. All rights reserved.
Results

Real Results Across Industries.

Not presentations. Not projections. These are data foundations operating live for global enterprises at scale.

60%
Cost reduction versus legacy platforms
CMS
97%
Gain in data processing efficiency
Edwards Lifesciences
10x
Larger addressable market with a Snowflake Native App
VGS
Client results
More proof on the platform.
Snowflake migrations and data products delivered across industries, at enterprise scale.
Client
Snowflake build
Result
US Foods
Supply Chain
Oracle Exadata to Snowflake and Amazon Web Services modernization, with standardized ingestion and DataOps.
$10M
EBITDA impact. 1000x faster report rationalization.
CMS
Government
Legacy federal data estate modernized onto Snowflake, with more than two petabytes validated.
60%
Lower cost. 85% gain in query efficiency.
Edwards Lifesciences
Healthcare
Snowflake pipeline modernization for a global medical technology leader.
97%
Data efficiency gain. Five-minute pipelines.
GXO Logistics
Supply Chain
Real-time Snowflake data platform processing 200 million signals per day.
40%
Faster speed to market. 25% larger addressable market.
VGS
Financial Services
Snowflake Native App turning proprietary data into a productized offering.
10x
Larger addressable market. 80% faster speed to market.
Komodo Health
Healthcare
Snowflake data products spanning 330 million de-identified patient journeys.
40%
Increase in clinical data visibility.
Century Distribution
Supply Chain
SQL Server to Snowflake migration with automated pipelines that removed manual error.
$121K
Annual savings. 10x lower DBA and operations time.
The Data Innovation Journey
01
Chaos
Data trapped in costly legacy warehouses, slow to query and hard to govern.
02
Order
A governed Snowflake foundation unifies the enterprise on one trusted data platform.
03
Insight
Teams query trusted data in minutes, with analytics and machine learning built on Snowflake.
04
Innovation
Native apps and data products turn the platform into new revenue and market reach.
Don't get left behind
© IBM Corporation 2026. All rights reserved.
Stage 01
Chaos
Data is scattered across siloed, legacy systems. No unified visibility. No reliable insight. No foundation for intelligence, automation, or modern AI innovation.
Stage 02
Order
A modern data stack is in place. Data is centralized, pipelines are clean, and the organization can finally trust what it’s looking at.
Stage 03
Insight
Data operates as a trusted asset across the organization. A single source of truth drives reliable intelligence, faster decisions, and measurable business impact at every level.
Stage 04
Innovation
Organizations at this stage have fully adopted and are operating on a modern data stack, deploying AI for automation and intelligence, launching data products, and opening revenue streams that weren’t possible before. With an AI-first infrastructure and mindset in place, they move fast on emerging technology that slower adopters can’t, leaving the competition behind.
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