Introduction
Toyota Financial Services’ Group BI team in Cologne supports financial reporting across nine European countries. To create a single source of truth for regulatory reporting and performance measurement, they needed to modernize their data warehouse, standardize inbound data, and move to a scalable cloud architecture on Snowflake.
“ At seven months into the project we can say it really worked out. We have been able to really quickly develop an initial MVP for our first country and that was really good. The automation and the changes we needed to do were rapidly applied. We had to remodel a few things and that was done within a day with the automation in WhereScape. ”
– Carsten Griefnow, Senior BI Manager, Toyota Financial Services
Pre-WhereScape Challenges
- Fragmented models: Each country had its own data model, creating inconsistencies and reconciliation overhead.
- Inconsistent delivery: Data arrived in different formats and frequencies, ranging from daily to monthly.
- Legacy platform limits: IBM Informix and an on-prem harmonization layer were not scalable or time-efficient.
- Manual ETL burden: Pentaho ETL tool, plus hand-coding slowed delivery and made change harder to manage.
- Need for standardization: The team wanted daily delivery in a common XML format to reuse sourcing patterns.
- Proof pressure: Vendors had to prove they could rebuild an interface feed faster from a calculation engine.
Why WhereScape?
The team needed to shift from hand-coded ETL to repeatable, automated ELT with strong governance. WhereScape fit because it supports Data Vault modeling, accelerates build and change through automation, and captures every action in a metadata repository, enabling documentation, data lineage, and impact analysis that supports regulatory reporting requirements.
“ WhereScape is majorly different from a classic ETL tool. You need to switch your mindset to understand what you’re looking for. I have multiple countries doing the same process over and over again, so is there a way of automating it where you can streamline it to do the development once, then reapply it for every country in the same way? This is where WhereScape comes into play. ”
– Carsten Griefnow, Senior BI Manager, Toyota Financial Services
The Solution
Snowflake + Data Vault Ecosystem
WhereScape partner, Infomotion recommended a data ecosystem combining Snowflake’s cloud data platform, Data Vault modeling, and WhereScape Data Automation to build and operate the enterprise data warehouse with repeatable patterns.
Proof Of Concept Delivery
Vendors were challenged to rebuild an interface feed and harmonize the data for loading. Infomotion delivered a result that fit seamlessly; a competitor using an AWS ETL tool did not reach a fit-for-purpose outcome.
Automated ELT With WhereScape RED
The team moved from Pentaho hand-coded ETL to automated ELT. WhereScape generated Snowflake DDL, supported scheduling and loading, and reduced friction when extending the same process across multiple countries.
Model-Driven Development With 3D
WhereScape 3D and RED supported designing and building a Data Vault from scratch, enabling faster iteration when requirements shifted and remodels were required during delivery.
“ I was working with ETL tools like Informatica Data Services for the last eight years, so it’s a bit different. The first country would have been easier to do it by hand, but the extension of the whole loading process is super easy with WhereScape and I really like that it’s all done in one program. ”
– Daniel Bredfeldt, Consultant at WhereScape partner Infomotion
Results
🚀 Cloud Migration Progress
- 95% of infrastructure moved into Snowflake within the first 7 months.
- The team positioned Snowflake compute to scale up or down based on need.
- WhereScape was also deployed in cloud infrastructure to support the new model.
🚀 Faster Delivery And Change
- An initial MVP for the first country was delivered quickly within the project window.
- Remodels were completed within a day using WhereScape automation.
- Data Vault modeling and loading were built quickly from scratch.
🚀 Governance For Regulatory Reporting
- Every action captured in a metadata repository for traceability and repeatability.
- Built-in data lineage supported end-to-end regulatory reporting requirements.
- Impact analysis and tracing simplified change management and audits.
🚀 Documentation That Stays Current
- Automated documentation reduced a persistent delivery pain point.
- Documentation could be produced at any point, not as an end-of-project scramble.
- Better visibility improved confidence across teams and country stakeholders.
Standardized XML Feeds
A major step in harmonization was requiring countries to deliver reporting data in a standardized XML format. This improved consistency, reduced per-country variance, and made it possible to reuse sourcing and loading logic across the multi-country footprint rather than rebuilding pipelines repeatedly.
From On-Prem To Future-Proof
The team initially considered an updated on-prem approach (Pentaho and Oracle), but management pushed for a future-proof cloud strategy. Snowflake provided the target cloud data platform, while WhereScape provided the data warehouse automation layer to generate and manage ELT patterns and Data Vault structures.
A Mindset Shift To Automation
Moving from hand-coding and traditional ETL tools to a model-driven, metadata-first approach required adjustment, especially for developers accustomed to writing source code directly. Once the team aligned on patterns and automation, the benefits became clearer: faster extensions, easier reruns, and smoother deployment.
