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Customer Success Story
Comprehensive AWS Data and Analytics Solution
Client
A leading provider in the waste management sector, delivering solutions for efficient waste collection, recycling, and disposal to enhance operational efficiency & sustainability.
Business Challenge
- Unintegrated data sources cause scattered reporting and manual consolidation.
- Decentralized platform hinders data management and access control.
- Manual data processes lead to delays and inconsistencies.
- Disjointed platform needs modernization for real-time fleet data.
- Lack of advanced analytics limits proactive decision-making.
Business Objective
Consolidate diverse data sources into an AWS S3 data lake for a single source of truth.
Leverage Amazon S3's scalability and durability for efficient data storage and management.
Utilize AWS analytics services for big data processing and machine learning capabilities.
Enable real-time data ingestion and processing
Enhance decision-making through insights from KPI’s and optimized operations.
Approach
- Delivered a fully-integrated, AWS-native data and analytics platform for real-time decision-making.
- Designed the platform following AWS's Well-Architected Framework for a secure data foundation.
- Built a robust data lake using AWS Glue for seamless data integration & management.
- Implemented serverless, event-driven architecture with AWS Lambda for automated data processing.
- Integrated diverse data sources, including IoT, fleet management, & ERP systems.
- Utilized AWS Glue to catalog datasets for efficient metadata analysis & schema management.
- Developed 360-degree analytics around customers, vehicles, and drivers using AWS services.
- Monitor performance and costs with CloudWatch for proactive infrastructure management.
Technology Components
Compute
AWS Lambda
AWS Glue
Data Integration
AWS Glue
AWS CodePipeline
Storage
Amazon S3
Amazon Redshift
Analytics
Amazon Athena
Amazon QuickSight
Monitoring
Amazon CloudWatch
Transformational Effects
25%
Cost Saving
$80+
Saved in License Costs
40%
Reduced issue resolution time
30+
Reduced operational costs
- Achieved over 25% cost savings by utilizing Amazon S3 intelligent Tiering for data storage, cleaning & curation
- Saved $80K+ in license costs by migrating workloads from Cloud ETL to AWS Glue and Kinesis
- Reduced issue resolution time by 40% through automated monitoring of Glue workloads
- Reduced operational costs by an estimated 30% via adoption of serverless technologies
Ready to Transform Your Data Platform?
Let's discuss how we can help you build a modern data architecture that drives business value