Data Lakehouse Platform Development & Staff Augmentation for Yara
Services Covered:

Agriculture
26 months
50K - 199K
1 June 2024
1-5 Employees
Nearshore
Project Capability Score (PCS)
Project Capability Score (PCS) estimates how capable SENLA is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS
Client
YARA GmbH & Co. KG
Project Summary
Key Challenges
- Consolidate data from multiple sources, including different Yara product data.
- Provide employees with easy access to analyze and work with consolidated data via a user-friendly interface.
- Build the platform using a Data Lakehouse methodology to support analytical needs.
Project Deliverables
- Data platform
- Infrastructure on Amazon AWS managed with Terraform
- Data processing pipelines implemented in Python
- Data Lakehouse methodology implementation
Project Solution
Project Outcome
- Team consistently met deadlines and worked seamlessly with internal stakeholders.
- Communication was clear and frequent, keeping stakeholders informed.
- The vendor was flexible with staffing needs and aligned on meetings and syncs.
- Their expertise in Data Lakehouse methodologies improved data management and analysis.
- Strong cultural fit and commitment fostered continued collaboration.
Platforms
Cloud
Tech Stack
PythonAmazon Web Services (AWS)
Client Endorsement
Overall Review Rating
Timeliness
Cost Rating
Willing to Refer
Quality of Deliverables
“SENLA’s team has successfully completed the project. So far, they've met deadlines, communicated clearly and frequently, worked seamlessly with internal stakeholders, and proven a strong cultural fit. Overall, the team's drive to go the extra mile has set the foundation for further collaboration.”
Note: This endorsement is based on publicly available client feedback from external review sources.
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