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Case Study

Migrations of Analytics Workload from AWS to GCP

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Key Takeaways

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Migrating to GCP for large-scale data processing

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Built a data lake for reporting, ML, and analytics

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Used Kafka and Spark for real-time data pipelines

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Implemented a centrally managed data lake with live data for analysis

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Modern Architecture

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Creation of ML algorithms to forecast early in the process & developed prescriptive models to suggest process

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Real-time video and image processing model to detect the car's make and severity of the damage
 

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Automation of manual verification that scans building plans as input and used computer vision to extract spec

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