Syngenta
Building a Scalable Hub-and-Spoke Enterprise Data Platform on AWS
Client Overview
Syngenta is a leading global agriculture company focused on sustainable farming solutions across crop protection, R&D, and supply chain operations. The organization required a scalable, governed enterprise data platform to eliminate data silos, improve data accessibility, and enable modern analytics while maintaining centralized governance and security across business domains.
BUSINESS CHALLENGE:
Syngenta faced several challenges in scaling its enterprise analytics platform:
• Data Silos: Business domains maintained independent datasets, resulting in inconsistent reporting and limited enterprise visibility.
• Limited Self-Service Analytics: Business users relied heavily on centralized engineering teams to access trusted data.
• Scalability Constraints: Existing data pipelines struggled to accommodate increasing data volumes and new data sources.
• Governance Challenges: Standardized metadata management, access control, and data quality processes were required across all business domains.
• Operational Complexity: A standardized platform was needed to simplify onboarding of new business domains while maintaining consistent security, governance, and operational practices.
OUR SOLUTION:
Celebal Technologies designed and implemented a scalable Hub-and-Spoke Enterprise Data Platform on AWS. AWS Glue was used to ingest enterprise data into an Amazon S3-based data lake, where Business Hub teams transformed data through Bronze, Silver, and Gold layers using Databricks. The Enterprise Platform Team established centralized governance, security, monitoring, and operational standards, while Business Hubs independently developed and managed their analytical workloads.
Curated Gold datasets were made available through Amazon Athena for ad hoc analytics, Amazon Redshift for enterprise reporting, Amazon QuickSight for business dashboards, and Amazon SageMaker for centralized machine learning use cases.
The solution leveraged the following AWS services:
• Amazon S3:Enterprise data lake for Bronze, Silver, and Gold datasets.
• AWS Glue: Data ingestion, orchestration, and metadata management.
• Amazon Athena: Serverless SQL analytics on curated datasets.
• Amazon Redshift: Enterprise reporting and curated analytical views.
• Amazon QuickSight: Business intelligence dashboards and reporting.
• Amazon SageMaker: Centralized machine learning model development.
• AWS IAM, AWS KMS & AWS Lake Formation: Identity, security, encryption, and fine-grained data governance.
• Amazon CloudWatch, AWS CloudTrail & AWS Config: Operational monitoring, auditing, and compliance.
• Databricks on AWS:Distributed data processing and business-domain data transformation.
Benefits
Faster Business Hub Onboarding
Standardized platform services, governance controls, and reusable implementation patterns accelerated onboarding of new business domains.
Improved Data Accessibility
Curated Gold datasets enabled trusted self-service analytics through Amazon Athena, Amazon Redshift, and Amazon QuickSight.
Standardized Governance
Centralized identity, security, metadata management, and access control established consistent governance across the analytics platform.
Scalable Analytics Platform
AWS managed services and distributed processing enabled the platform to scale with growing data volumes and analytical workloads.
Enhanced Operational Visibility
Centralized monitoring, logging, and operational dashboards improved platform reliability and simplified incident management.
Reusable Enterprise Framework
Standardized architecture, deployment patterns, and governance processes reduced implementation effort for future analytics initiatives.
Celebal Technologies implemented a scalable AWS-based Hub-and-Spoke Enterprise Data Platform that enabled secure, governed, and self-service analytics while simplifying platform operations. The standardized architecture improved data accessibility, strengthened governance, accelerated onboarding of new business domains, and established a reusable foundation capable of supporting future enterprise analytics and AI initiatives.
