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Google Cloud : Modernizing Data Lakes & Data Warehouses with Google Cloud Platform

  • Learned to distinguish between data lakes and data warehouses and when to use each in real business settings

  • Explored cloud-based storage architectures and analytics strategies to support scalable data ecosystems on GCP

  • Understood how to design and manage pipelines and integrate raw/unprocessed data with structured analytics systems

  • 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:

  • Cloud Storage / Google Cloud Storage for raw and archival data

  • BigQuery as a data warehouse solution

  • Pipeline design patterns for ETL / ELT and data ingestion

  • Integration of data lakes and warehouses over GCP

  • Modular architecture strategies (schema, data partitioning, performance tuning)

  • Query optimization and data modeling for analytics workloads

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