While the direct Udemy link is protected from automated scraping, the official course outline and curriculum details reveal exactly what this production-grade project covers.
Created by Shaik Saidhul (SkillVane IT Academy), “End-to-End GCP Data Engineering Project – Banking Domain” is a comprehensive, practical course designed to simulate how modern financial institutions process millions of transactions securely and efficiently using Google Cloud Platform (GCP).
Course Overview & Key Focus
The course focuses heavily on building robust Batch and Real-Time Data Pipelines from scratch using an industry-standard banking use case. Instead of working with simple, clean CSV files, you will build a resilient data architecture that mirrors production environments.
Core Concepts & Architecture Covered
- Dual Processing Pipelines: Deep高度 dives into both Batch processing (for historical reconciliation) and Streaming data processing (for instant transaction tracking).
- Change Data Capture (CDC): Capturing database changes instantly to stream transaction details securely.
- Medallion Architecture: Structuring your data warehouse into organized layers: Bronze (Raw data ingestion), Silver (Cleaned and transformed data), and Gold (Business-ready aggregates).
- Data Modeling: Implementing Fact and Dimension Modeling along with Slowly Changing Dimensions (SCD Type 2) to maintain a perfect historical record of bank account changes.
- Metadata-Driven Framework: Building reusable pipelines controlled by metadata config files rather than hardcoded logic.
- Production Standards: Implementing comprehensive logging, automated alerting, exception handling, and real-time fraud detection analytics.
GCP Tools & Technologies You’ll Learn
- Dataflow & Apache Beam: For serverless, scalable stream and batch processing.
- Dataproc & PySpark: Running big data transformations using managed Spark clusters.
- BigQuery: Setting up an enterprise data warehouse for analytical reporting.
- Cloud Composer (Apache Airflow): Orchestrating the entire workflow and scheduling pipelines.
- CI/CD Pipelines: Automating updates using Cloud Build and GitHub Actions.
