DATA MODERNIZATION
Outcomes
The foundation for innovation.
The cost of staying on aging infrastructure compounds. Slower decisions, higher maintenance, and an inability to run the systems your competitors are already deploying. We build the foundation so companies can run today’s analytics, AI, and data products, and quickly implement what’s coming next.
Before
Legacy on-premise infrastructure restricted growth. Nightly processing took hours, cloud experience was limited, and a 9-month rewrite was planned.
FIS · Financial Services
→
After
Planned 9-month rewrite delivered in 4 months. Nightly processing reduced from hours to minutes. Near real-time reporting enabled across the organization.
9-month rewrite delivered in 4 months
Before
All data sat on AWS with performance issues and inefficient pipelines. No ability to build data products or monetize the data estate.
Transbank · FinTech / Payments
→
After
AWS-to-Snowflake migration completed. First data products in production in under one month. First public-facing application live within two months. A dormant data estate transformed into an active revenue platform.
35% faster to market · $250B new TAM unlocked
Before
BI platform built on 49 Essbase cubes. Hard to scale, performance challenges, and governance gaps across a major CPG operation.
Perdue Farms · CPG
→
After
49 Essbase cubes converted to relational facts and dimensions. 762 governance-approved metrics on a centralized Snowflake data model. BI platform fully modernized.
762 metrics centralized · full governance approved
Our approach
The systems you run are only as good as the infrastructure they’re built on. We modernize data infrastructure that companies need to run today’s workloads and tomorrow’s innovations.

We architect your data foundation so every platform, pipeline, and model built on it performs. Built on Snowflake, dbt, and IBM watsonx.

© IBM Corporation 2026. All rights reserved.
Systems
Migrate. Modernize. Monetize.
Every automation follows a specific architecture. Data flows in, AI processes it in real time, and the right output reaches the right person, agent, or system. Each implementation is tailored to the client's data and workflow.
View Example Architectures →
Not lift-and-shift
Architecture from the ground up
We don't copy your old architecture into a new environment. Every migration includes schema redesign, pipeline optimization, and governance built in from the start.
Not fragmented
Unified data
Siloed systems, inconsistent schemas, and duplicated logic get consolidated into a single governed platform. One source of truth across every domain.
Not disruptive
Zero-downtime delivery
We don't take your systems offline to modernize them. Migrations run in parallel, with cutover only after full validation and sign-off.
Not static
Future-ready
Every modernization is designed with your roadmap in mind. The architecture scales with your roadmap, not just your current workload.
“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.
Success
Real Results Across Industries.
Not presentations. Not projections. These are production data modernization engagements live for global enterprises at scale.
$250B
New total addressable market unlocked
Transbank
35%
Faster speed to market post-migration
Transbank
56%
Reduction in platform rewrite time
FIS
Client results
More results, more industries.
Data modernization engagements delivered across financial services, banking, healthcare, CPG, supply chain, and food distribution.
Client
Modernization type
Result
FIS
Financial Services
Legacy on-prem to Snowflake pipeline rewrite using dbt models and cloud-optimized tooling. Near real-time semantic layer refresh delivered via co-development.
9-month rewrite in 4 months Nightly processing from hours to minutes
Texas Capital Bank
Banking
Three siloed data sources consolidated into Snowflake Data Vault. Modern data architecture, data quality maturity, and end-to-end governance implemented.
72% reduction in implementation efforts - end-to-end governance in 5 months
Transbank
FinTech / Payments
AWS-to-Snowflake migration. First data products in production in under one month. First public-facing application live within two months.
35% faster to market $250B total addressable market unlocked
US Foods
Food Distribution · 28,000 employees
Oracle Exadata to Snowflake migration. 6,000 users moved from Oracle BI to Sigma. Enterprise reporting portal established. Legacy tech debt retired.
1,000x faster report rationalization - 2x program investment payback by year 2
NextGen Healthcare
Healthcare Technology
AI-assisted database rationalization and Snowflake migration across three core products. Complex AWS infrastructure simplified and costs reduced.
$1.5M saved in estimated operational costs
Perdue Farms
CPG
49 Essbase cubes converted to relational facts and dimensions on Snowflake. Centralized data model with 762 governance-approved metrics.
Structural proof
Governance-approved metric centralization complete. BI platform fully modernized.
CardWorks
Financial Services / Lending
Greenplum to Snowflake migration using SnowConvert and automated testing. 6TB compressed data, 805 tables, 220 views, and 21 functions migrated in 4.5 months.
Structural proof
Greenplum environment fully retired. Legacy tech debt eliminated.
HPS Investment Partners
Capital Markets
Legacy SQL Server on-prem to modern data stack. Reusable ingestion and modeling patterns. Automated CI/CD and orchestration deployed.
Structural proof
24-month roadmap with Cortex integrations underway. Reusable patterns accelerating every new domain.
Take a Look
Vertical TBD
Data Modernization Video 1
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Vertical TBD
Data Modernization Video 2
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The Data Innovation Journey
Stage 01
Chaos
→
Stage 02
Order
→
Stage 03
Insight
→
Stage 04
Innovation
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 are positioned to move faster on emerging technology than slower adopters can, leaving the competition behind.