Restaurant Chain Consolidates Data Infrastructure with AWS and Snowflake Migration
A national restaurant chain engaged CONVX to migrate a subsidiary brand's data infrastructure from a separate AWS account into the parent company's standardized AWS services and Snowflake data warehouse.
A restaurant chain undergoing data infrastructure migration · client anonymized · Project · Standard engagement · 2 min read
Client Overview
A national restaurant chain engaged CONVX to migrate a subsidiary brand's data infrastructure from a separate AWS account into the parent company's standardized AWS services and Snowflake data warehouse. The consolidation eliminated data silos, unified reporting, and established a modern data architecture across the organization.
Business Challenge
Fragmented Data Infrastructure: Following an acquisition, the subsidiary brand operated its own separate AWS account with independent data pipelines and analytics, creating data silos that prevented unified business intelligence across brands.
Data Warehouse Modernization: The subsidiary's existing data infrastructure needed to be replatformed to align with the parent company's Snowflake data warehouse and standardized analytics stack.
Schema Restructuring: Legacy data structures required transformation into a star schema design to support efficient analytical queries and reporting within the consolidated data warehouse.
CONVX Solution Approach
CONVX delivered end-to-end data infrastructure migration consolidating the subsidiary's data operations into the parent company's modern data platform.
Data Pipeline Replatforming: We migrated existing data pipelines from the subsidiary's AWS account to the parent company's standard AWS services, leveraging Lambda, S3, and ECS Fargate for efficient data processing.
Athena View Replication: Existing Amazon Athena views were analyzed and replicated in the target environment, ensuring continuity of existing query patterns and analytics workflows during the transition.
Star Schema Restructuring: Data models were redesigned into a star schema architecture within Snowflake, optimizing the data structure for analytical performance and enabling unified reporting across both brands.
Tableau Integration: The migrated data warehouse was integrated with Tableau for business intelligence and reporting, providing stakeholders with consolidated dashboards across the organization.
Technology Implementation
- AWS Lambda, S3, and ECS Fargate data pipelines
- Amazon Athena view migration
- Snowflake data warehouse implementation
- Star schema data model design
- Tableau business intelligence integration
- Data pipeline architecture and orchestration
Business Outcomes
Unified Data Platform: Consolidated data infrastructure eliminates brand-level data silos, enabling cross-brand analytics and unified business intelligence.
Modern Data Architecture: Star schema design in Snowflake provides an optimized analytical foundation that scales with business growth and supports advanced reporting needs.
Operational Efficiency: Standardized AWS services and centralized data pipelines reduce infrastructure management overhead and eliminate the cost of maintaining a separate AWS account.
CONVX Expertise Demonstrated
This engagement demonstrates CONVX's expertise in data infrastructure migration and warehouse modernization for multi-brand organizations. Our ability to replatform data pipelines, restructure data models, and consolidate cloud infrastructure enables companies to achieve unified analytics and eliminate the technical debt created by acquisitions and fragmented data systems.