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Welcome to the DE Project Blog

This blog provides step-by-step project documentation for data engineering workflows.
Each project is organized into clear sections: Overview, Data Exploration, Modeling, Code Templates, Orchestration, and Deployment.

📂 Projects

✈️ Airline Project

  • Overview → High-level goals, architecture, and dataset description.
  • Infrastructure → Architecture diagrams, provisioning, and infra notes.
  • Data Exploration → Profiling airline data, identifying patterns, and preparing features.
  • Modeling → Building predictive models (e.g., delays, pricing, demand forecasting).
  • Code Templates → Reusable ETL scripts, transformation modules, and pipeline snippets.
  • Orchestration → Workflow automation with schedulers (Airflow/NiFi).
  • Deployment → Release notes, production rollout, and monitoring strategies.

📊 Market Data Project

  • Overview → Scope of market datasets, sources, and objectives.
  • Data Exploration → Analyzing raw feeds, cleaning, and enrichment.
  • Modeling → Statistical and ML models for trends, anomalies, or forecasting.
  • Code Templates → Standardized ingestion and transformation scripts.
  • Orchestration → Pipeline scheduling and dependency management.
  • Deployment → Versioned releases, dashboards, and operational monitoring.

💹 Stock Prices Project

  • Overview → Documentation of stock datasets and project scope.
  • Data Exploration → Exploratory analysis of stock price movements.
  • Modeling → Time-series models, regression, or ML-based predictions.
  • Code Templates → Reusable modules for financial data pipelines.
  • Orchestration → Automated workflows for daily/weekly updates.
  • Deployment → Release notes, monitoring, and alerting for production pipelines.

📁 Other Projects