
Google Cloud : Modernizing Data Lakes & Data Warehouses with Google Cloud Platform
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Learned to distinguish between data lakes and data warehouses and when to use each in real business settings
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Explored cloud-based storage architectures and analytics strategies to support scalable data ecosystems on GCP
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Understood how to design and manage pipelines and integrate raw/unprocessed data with structured analytics systems
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Gained insight into the role of a data engineer and how modern data architectures support operational and strategic decisions
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Tools & Techniques:
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Cloud Storage / Google Cloud Storage for raw and archival data
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BigQuery as a data warehouse solution
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Pipeline design patterns for ETL / ELT and data ingestion
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Integration of data lakes and warehouses over GCP
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Modular architecture strategies (schema, data partitioning, performance tuning)
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Query optimization and data modeling for analytics workloads
