1 | Predictive Maintenance for Manufacturing | High maintenance costs and frequent machine breakdowns affecting production | Implemented IoT sensors and machine learning models for predictive maintenance, reducing equipment failures before they occur | – Reduced downtime by 35%
– Decreased maintenance costs by 25%
– Improved production efficiency | AWS IoT, Apache Spark, AWS SageMaker |
2 | Legacy System Modernization for Healthcare | Outdated patient data management systems leading to inefficiencies and compliance risks | Migrated legacy system to a cloud-based architecture with secure data pipelines for patient management and analytics | – Enhanced data accessibility
– Improved compliance with healthcare regulations
– Reduced operational costs by 30% | GCP, Apache NiFi, Google BigQuery |
3 | Cloud-Based Data Lake for Centralized Data Management | Data silos across departments limiting access and analysis capabilities | Built a cloud-based data lake for centralized data storage, improving accessibility and quality for unified reporting | – Improved cross-department insights
– Reduced storage costs
Enabled advanced analytics | AWS S3, AWS Glue, Amazon Redshift |
4 | Dynamic Pricing Optimization for Hospitality | Needed dynamic pricing to maximize revenue and occupancy | Built a pricing optimization model to adjust prices based on factors like occupancy, competitor pricing, and seasonal demand | – Increased revenue per room by 15%
– Improved occupancy rate by 10%
– Enhanced pricing adaptation to market conditions | Google AI Platform, Google Cloud Pub/Sub, Google Data Studio |
5 | Supply Chain Optimization for Retail Distribution | Inventory shortages and overstock issues impacting profitability | Developed a demand forecasting and inventory management model to optimize distribution routes | – Reduced inventory costs by 20%
– Minimized stockouts and overstock situations
– Improved customer satisfaction | Azure Machine Learning, Power BI, SQL databases |
6 | Lift and Shift Cloud Migration of 10TB Data | High maintenance costs and limitations with on-premises infrastructure | Executed lift and shift migration to AWS for 10TB of data, using AWS Snowball for data transfer and AWS DMS for database migration | – Reduced operational costs by 40%
– Enhanced data security
– Improved disaster recovery and scalability | AWS Snowball, AWS Database Migration Service, Amazon S3, AWS IAM, AWS KMS |
7 | Real-Time Customer Segmentation for E-commerce | Struggled with real-time customer segmentation for targeted marketing | Built a data pipeline for continuous customer segmentation based on behaviour, purchase history, and demographics | – Enhanced engagement through targeted promotions
– Increased conversion rate by 20%
– Reduced marketing costs | Apache Kafka, Google BigQuery, Elastic Search |
