Toptal cuts data query processing time from hours to 30 minutes for leading research institution.
Faced with inefficient data preprocessing due to ad-hoc coding, a prestigious research institution enlisted Toptal to deliver a streamlined and secure solution.
Client
A Germany-based scientific research organization advancing fundamental knowledge across multiple disciplines worldwide.
Employees
Revenue
Industry
ResearchDelivered Services
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The institution struggled with a cumbersome data preprocessing workflow due to unstructured coding and local code execution.
Solution
Modular Codebase Redesign
Toptal restructured the codebase into a modular, production-ready system with logging features, optimizing management and execution, and using MongoDB to cut processing times.
Systematic MongoDB Pipeline
Toptal implemented MongoDB pipelines in a Python environment to streamline operations, removing dependencies on local machines and improving data accessibility and security.
Outcome
Significant Time Reduction
The transformation reduced data query processing times from hours to 30 minutes, allowing researchers to concentrate more on core tasks by easing data handling burdens.
Improved Data Management
Incremental processing methods optimized data management, processing only essential data, which enabled better practices and paved the way for innovative research methodologies.
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