SUCCESS STORY｜RAG & BONE
Rag & Bone｜Data platform optimization and getting ready for AI
A premium New York fashion brand, Rag & Bone asked KPC Canada to optimize its data platform: rolling out the Supply Chain datamart and a semantic layer, for a foundation ready for AI.
The impact in numbers
3
domains rebuilt
sales, inventory, finance
1
Supply Chain datamart
optimized
1
semantic layer
agnostic
AI-ready
a foundation ready for
future AI projects
The impact in numbers
3
domains rebuilt
sales, inventory, finance
1
Supply Chain datamart
optimized
1
semantic layer
agnostic
AI-ready
a foundation ready for
future AI projects
The impact in numbers
3
domains rebuilt
sales, inventory, finance
1
Supply Chain datamart
optimized
1
semantic layer
agnostic
AI-ready
a foundation ready for
future AI projects
RESULTS
Three concrete benefits for Rag & Bone
Costs reduced and better controlled
Lower, better-controlled data platform costs.
Three concrete benefits for Rag & Bone
Simpler maintenance of KPIs and business rules
The calculation rules behind the key indicators are simpler to maintain and to evolve.
Three concrete benefits for Rag & Bone
Analytical performance improved
Faster analysis and reporting, on a data foundation that is reliable, scalable and ready for future AI projects.
RESULTS
Three concrete benefits for Rag & Bone
Costs reduced and better controlled
Lower, better-controlled data platform costs.
Three concrete benefits for Rag & Bone
Simpler maintenance of KPIs and business rules
The calculation rules behind the key indicators are simpler to maintain and to evolve.
Three concrete benefits for Rag & Bone
Analytical performance improved
Faster analysis and reporting, on a data foundation that is reliable, scalable and ready for future AI projects.
RESULTS
Three concrete benefits for Rag & Bone
Costs reduced and better controlled
Lower, better-controlled data platform costs.
Three concrete benefits for Rag & Bone
Simpler maintenance of KPIs and business rules
The calculation rules behind the key indicators are simpler to maintain and to evolve.
Three concrete benefits for Rag & Bone
Analytical performance improved
Faster analysis and reporting, on a data foundation that is reliable, scalable and ready for future AI projects.
Background & core challenges
A data platform that had become expensive, heavy to maintain and slow
Founded in New York in 2002, Rag & Bone is an American fashion brand in the premium segment. It stands out for its balance of craft heritage, quality standards and creative innovation, with an international presence and omnichannel sales.
Against a backdrop of growth and fine-grained performance management (sales, inventory, supply chain), the brand leans heavily on data to track its key indicators, streamline operations and support strategic decisions.
The rapid growth in data volumes and the variety of analytical uses, however, exposed the limits of the existing platform, in cost, maintainability and performance alike.
Take back control of the platform's operating costs
Simplify maintenance of the calculation rules behind the key indicators
Speed up loading and reporting for the business teams
Build a reliable, structured and scalable foundation, ready for future AI use cases
Background & core challenges
A data platform that had become expensive, heavy to maintain and slow
Founded in New York in 2002, Rag & Bone is an American fashion brand in the premium segment. It stands out for its balance of craft heritage, quality standards and creative innovation, with an international presence and omnichannel sales.
Against a backdrop of growth and fine-grained performance management (sales, inventory, supply chain), the brand leans heavily on data to track its key indicators, streamline operations and support strategic decisions.
The rapid growth in data volumes and the variety of analytical uses, however, exposed the limits of the existing platform, in cost, maintainability and performance alike.
Take back control of the platform's operating costs
Simplify maintenance of the calculation rules behind the key indicators
Speed up loading and reporting for the business teams
Build a reliable, structured and scalable foundation, ready for future AI use cases
Background & core challenges
A data platform that had become expensive, heavy to maintain and slow
Founded in New York in 2002, Rag & Bone is an American fashion brand in the premium segment. It stands out for its balance of craft heritage, quality standards and creative innovation, with an international presence and omnichannel sales.
Against a backdrop of growth and fine-grained performance management (sales, inventory, supply chain), the brand leans heavily on data to track its key indicators, streamline operations and support strategic decisions.
The rapid growth in data volumes and the variety of analytical uses, however, exposed the limits of the existing platform, in cost, maintainability and performance alike.
Take back control of the platform's operating costs
Simplify maintenance of the calculation rules behind the key indicators
Speed up loading and reporting for the business teams
Build a reliable, structured and scalable foundation, ready for future AI use cases
Our approach
A data foundation rethought, from warehouse to semantic layer
From Montreal, KPC Canada rethought Rag & Bone's data platform to cut costs, simplify maintenance and get it ready for AI.
Migration & Architecture
Rebuilding the warehouse and migrating to Oracle
Rebuilding the sales, inventory and finance data warehouse, and migrating the data platform from Azure SQL to Oracle.
Semantic layer
An agnostic semantic layer
A market study, then the implementation of an agnostic semantic layer, independent of the underlying technologies.
Our approach
A data foundation rethought, from warehouse to semantic layer
From Montreal, KPC Canada rethought Rag & Bone's data platform to cut costs, simplify maintenance and get it ready for AI.
Migration & Architecture
Rebuilding the warehouse and migrating to Oracle
Rebuilding the sales, inventory and finance data warehouse, and migrating the data platform from Azure SQL to Oracle.
Semantic layer
An agnostic semantic layer
A market study, then the implementation of an agnostic semantic layer, independent of the underlying technologies.
Our approach
A data foundation rethought, from warehouse to semantic layer
From Montreal, KPC Canada rethought Rag & Bone's data platform to cut costs, simplify maintenance and get it ready for AI.
Migration & Architecture
Rebuilding the warehouse and migrating to Oracle
Rebuilding the sales, inventory and finance data warehouse, and migrating the data platform from Azure SQL to Oracle.
Semantic layer
An agnostic semantic layer
A market study, then the implementation of an agnostic semantic layer, independent of the underlying technologies.
Our clients
Our clients
They trust us.
They trust us.
Equipment rental
Professional Equipment Rental Company | Industrialized tender response 100% Snowflake
Gen AI
Snowflake
→
Transport & Logistics
Global shipping company — Data Science: from R&D to industrialization
AI
Data
→
Industry
Aqualung Group — Transforming the data platform
Snowflake
Data Platform
→
Business services
APAVE — Cross-office capacity planning
Pigment
EPM
→
Organic food distribution
Biocoop — Steering the forecasting processes with SAP BPC
SAP
Retail & Distribution
→
Heating, plumbing and renewable energy distribution
Richardson — Opening up access to data by moving to the cloud
Qlik
Snowflake
→
Equipment rental
Professional Equipment Rental Company | Industrialized tender response 100% Snowflake
Gen AI
Snowflake
→
Transport & Logistics
Global shipping company — Data Science: from R&D to industrialization
AI
Data
→
Industry
Aqualung Group — Transforming the data platform
Snowflake
Data Platform
→
Business services
APAVE — Cross-office capacity planning
Pigment
EPM
→
Organic food distribution
Biocoop — Steering the forecasting processes with SAP BPC
SAP
Retail & Distribution
→
Heating, plumbing and renewable energy distribution
Richardson — Opening up access to data by moving to the cloud
Qlik
Snowflake
→
Equipment rental
Professional Equipment Rental Company | Industrialized tender response 100% Snowflake
Gen AI
Snowflake
→
Transport & Logistics
Global shipping company — Data Science: from R&D to industrialization
AI
Data
→
Industry
Aqualung Group — Transforming the data platform
Snowflake
Data Platform
→
Business services
APAVE — Cross-office capacity planning
Pigment
EPM
→
Organic food distribution
Biocoop — Steering the forecasting processes with SAP BPC
SAP
Retail & Distribution
→
Heating, plumbing and renewable energy distribution
Richardson — Opening up access to data by moving to the cloud
Qlik
Snowflake
→
A DATA FOUNDATION TO GET READY FOR AI?
A data platform that costs too much to maintain?
KPC supports you in optimizing your data platform, controlling its costs and getting ready for your future AI use cases.
A DATA FOUNDATION TO GET READY FOR AI?
A data platform that costs too much to maintain?
KPC supports you in optimizing your data platform, controlling its costs and getting ready for your future AI use cases.
A DATA FOUNDATION TO GET READY FOR AI?
A data platform that costs too much to maintain?
KPC supports you in optimizing your data platform, controlling its costs and getting ready for your future AI use cases.