
The project was commissioned by a globally recognized direct-selling beauty corporation, operating across 60 countries with millions of representatives worldwide. Their legacy data warehouse struggled to consolidate regional business data and adapt to changing market demands. Hiflylabs’ experts implemented a modern Data Vault architecture on the cloud, enabling real-time analytics and flexible business rule management across their global operations.
15x
cost savings migrating into the cloud from on-prem setup
4x
less menial tasks through automation, allowing more focus on strategy
1 week
to implement new business needs or integrate source systems, down from 3 months
The client faced the enterprise-scale challenge of consolidating diverse business data streams from over 60 countries worldwide. Their existing data warehouse, built with a rigid and traditional architecture, failed to adapt to evolving business definitions and couldn't support real-time analytics needs, nor could it preserve raw data historically.
The system's limitations obstructed long-term traceability of records, and meant that any changes to business rules, data structures or sources required months of development time. This severely impacted their ability to respond to changing market dynamics, historical analytics, and day-to-day workflows.
With daily operations processing millions of orders and tracking countless inventory changes, they required a solution that could handle information real-time, keep raw data intact, and enable agile adaptation to changing business needs.
Hiflylabs designed and implemented a Data Vault on a modern cloud infrastructure, overhauling all data operations. We replaced traditional ETL processes with a flexible lakehouse architecture, which solved both raw data preservation and adaptable business rules.
The solution features real-time data processing capabilities, supporting instant inventory updates and smart customer notifications. At its core, we developed a virtualized gold layer that empowers business stakeholders to create and modify analytics views without technical intervention. Since Data Vaults enable agile iterations, the new system can accommodate any business requirement flexibly, without the need of redesigning data pipelines from the grounds up.
Through automated data quality checks and processing workflows, we significantly reduced manual operational overhead. The scalable data structure we created easily supports new source systems and ad hoc business ideation. The new data platform transformed the client’s ability to handle complex multi-country operations while significantly reducing infrastructure costs.
Data
Retail
Python
Lambda
Athena
Wherescape
Glue
Tableau
Databricks
AWS
SQL
Python
Lambda
Athena
Wherescape
Glue
Tableau
Databricks
AWS
SQL
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