𝗣𝗿𝗲-𝗿𝗲𝗾𝘂𝗶𝘀𝗶𝘁𝗲𝘀

• SQL
• PL/SQL (Stored Functions, Stored Procedures, Indexes)
• Python
• Spark (PySpark, Spark SQL)

GCP 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀

• GCP Bucket:
  • Structured Data: e.g., Table Format (CSV, Excel)
  • Unstructured Data: e.g., Videos, Images, Text, PDFs
  • Semi-Structured Data: e.g., JSON Files
• Cloud SQL and cloud spanner:
• Google BigQuery:
• Dataflow:
• Apache Airflow
• Cloud Composer
• Dataprep:
• Dataproc:
• Cloud Data Fusion
• Google Pub/Sub:
• Machine Learning (ML) on GCP:
  • BigQuery ML:
  • Vertex AI:
• Data Lake & Delta Lake on GCP:
• DataOps on GCP:
• Data Visualization:
• Building ETL Pipelines:

𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 (At least 2)

1. Data Ingestion End-to-End Pipeline: using Cloud Composer, Dataflow, BigQuery, Pub/Sub
2. Data Ingestion End-to-End Pipeline: using other GCP services.

𝗔𝗧𝗦-𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝘁 𝗥𝗲𝘀𝘂𝗺𝗲

• Score: 80+

𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻

• Fundamental Concepts: Master both basic and advanced topics as outlined above.
• Scenario-Based Questions: Solve at least 100+ questions.

• Mock Interviews: Practice regularly.