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Customer Success Story
Geospatial Data Modernization Solution
Client
An American leading provider of Corridor Safety Intelligence, specializing in strengthening energy network resilience through innovative AI and multi-source data integration.
Business Challenge
- Outdated infrastructure/ scalability and performance for real-time satellite data processing.
- Fragmented storage systems create inefficiencies in data management.
- Lack of real-time data integration restricts analytics capabilities.
- Manual workflows reduce throughput and increase complexity.
- Security and compliance risks arise from a fragmented architecture.
Business Objective
Reduce power outages using advanced geospatial analytics.
Sought Mitigate fire and vegetation risks with satellite data.
Create a real-time risk management solution.
Automate infrastructure risk classification for efficiency.
Innovate continuously> through a geospatial ML lab.
Approach
- Analyzed the geospatial data platform with AWS and developed modernization blueprints.
- Migrated data from satellite imagery providers and on-prem systems to AWS analytics.
- Integrated cloud applications for improved performance and scalability.
- Automated real-time and scheduled data ingestion using serverless architecture.
- Used AWS Lambda and Fargate for event-driven processing and integration.
- Enabled advanced analytics with GeoSpatial Machine Learning in SageMaker.
- Stored spatial data in RDS PostgreSQL for analysis.
- Created an integrated architecture for scalable image processing and ETL pipelines.
Technology Components
Compute
AWS Lambda
AWS Fargate
AWS Glue
Storage
Amazon S3
RDS PostgreSQL
Data Processing & Analytics
Amazon SageMaker
Jupyter Notebooks
Data Management
MongoDB Atlas
Amazon Redshift
Transformational Effects
25%
Cost Saving
$150+
Saved in License Costs
15%
Reduced issue resolution time
10+
geospatial data products
- Achieved over 25% cost savings AWS Savings Plans and Reserved Instances for EC2 & Fargate workloads
- Saved $150K+ in license costs by migrating workloads from Cloud ETL to AWS Glue and Kinesis
- Reduced issue resolution time by 15% through automated monitoring of workloads
- Enabled 10+ geospatial data products like Vegetation Risk, Fire Potential, and Asset Audit
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