Case Study
Global Scaling & Legacy Transformation
How a global food and beverage manufacturer unified fragmented research data
The Situation
A global food and beverage manufacturer managed massive volumes of sensory and consumer data across dozens of regional teams. However, this knowledge was often trapped in fragmented Excel files with inconsistent templates. Identifying historical studies was a manual, error-prone process, leading to duplicated research and lost organizational memory.
How Does Infrastructure Standardization Eliminate Research Siloes?
In many global organizations, sensory and consumer data are trapped in “data siloes”: disparate Excel files with inconsistent templates, differing vendor formats, and no centralized search capability. This fragmentation leads to the duplication of efforts and a failure to apply historical learning. Transitioning to a unified infrastructure ensures that every study, regardless of its region or origin, contributes to the organization's collective intelligence.
Methodology: Unified Research Infrastructure
Aigora focused on transitioning data management from manual files to a structured, analytical platform built on three essential phases designed for enterprise scalability:
Unified Schema Development
The transformation began with the creation of a robust database schema. This architecture mapped relationships between diverse data types, including sensory descriptive data, consumer targets, and physical measurements, ensuring they could be combined and analyzed without friction.
Automated Ingestion & Cleaning
To handle the scale of global operations, manual data handling was replaced with an upgraded automated ingestion pipeline that:
- ●Standardize Formats:Translates various vendor outputs—specifically accommodating Compusense, EyeQuestion, FIZZ, and RedJade formats—into a consistent organizational template.
- ●Flag Inconsistencies: Automatically identifies missing mandatory fields or data inconsistencies before they enter the system.
- ●Enable User Correction: Provides an enhanced interface where researchers can input missing information and resolve common errors directly within the dashboard, significantly reducing the need to revisit original raw Excel files.
Modernized Access & Visualization
Centralized data accessed via a high-performance R Shiny interface hosted on the Posit platform, allowing global teams (including users in North America, Brazil, and China) to:
- ●Search Historically: Instantly identify past studies and conveniently pull or combine multiple studies for analysis.
- ●Automate Reporting:Generate analytical insights using a unified dashboard (the “SensoBox”).
- ●Maintain Security: Implement group-level access control to seamlessly manage dashboard access for individuals and regional teams.
Strategic Impact of Data Centralization
| Legacy Research Environment | Unified Research Infrastructure |
|---|---|
| Data stored in fragmented, unsearchable Excel files. | Data hosted in a secure, centralized Snowflake database. |
| Highly manual, time-consuming reporting processes. | Automated analytics via an interactive R Shiny dashboard. |
| Difficult to identify and reuse historical studies. | Instant historical search with the capability to cross-combine sensory and consumer databases. |
| Inconsistent methodologies across global teams. | Standardized templates ensure organizational consistency across global panels. |
Impact: Organizational Efficiency
Technical Foundation
This centralized research infrastructure leverages a robust, modern technology stack:
Backend & Processing: Built utilizing Azure Functions for serverless data processing and Snowflake for highly scalable, centralized database storage.
Frontend Dashboard: A user-friendly, interactive application built with R Shiny and deployed on the Posit SaaS platform to ensure seamless access, stability, and scalability for end users globally.
Ready to Transition Your Data Management to Living Infrastructure?
See how Aigora can turn fragmented legacy data into a centralized, compounding knowledge base that powers global decision making.