Articles
Page 5 of 6Practical guides on automation, ecommerce optimisation, and data engineering by Fawad Hussain Syed.
How to Build a CI/CD Pipeline for Data Workflows
Ship data pipeline changes with confidence using automated testing, linting, and deployment. Covers GitHub Actions, data validation gates, and rollback strategies.
Event-Driven Data Pipelines with Python and Redis
Build event-driven data pipelines that react to changes in real time using Python and Redis Streams. Covers pub/sub patterns, consumer groups, and backpressure handling.
How to Add Structured Logging to Python Data Pipelines
Replace print statements with structured logging that makes debugging production pipelines fast. Covers Python logging, structlog, JSON output, and correlation IDs.
Building a Lightweight Data Quality Framework from Scratch
Build a reusable data quality framework that scores datasets across completeness, accuracy, consistency, and timeliness — with trend tracking and automated alerting on quality degradation.
Containerizing Your Python Pipelines with Docker
Package your Python data pipelines into Docker containers for consistent, reproducible execution — from Dockerfile to docker-compose, with environment management and production deployment patterns.
How to Design Idempotent Data Pipelines That Are Safe to Re-Run
Build data pipelines that produce the same result whether they run once or ten times — using upserts, deduplication, and staging patterns in Python.
Web Scraping to Structured Data: Building Reliable Extraction Pipelines
Turn web pages into clean, structured data with Python — using resilient selectors, rate limiting, change detection, and robots.txt compliance for reliable extraction pipelines.
How to Schedule and Orchestrate Multi-Step Workflows with Prefect
Move beyond cron jobs — use Prefect to orchestrate data pipelines with dependency management, automatic retries, parallel execution, and a monitoring dashboard.
SQL for Data Engineers: Window Functions, CTEs, and Query Optimization
Go beyond SELECT * — master window functions, CTEs, and query optimization techniques that turn slow, convoluted SQL into fast, readable queries for reporting pipelines.
How to Build a Notification System That Actually Gets Read
Build a multi-channel notification system that routes alerts to Slack, email, and SMS based on severity — with deduplication, rate limiting, digests, and escalation so people do not ignore your alerts.
Real-Time vs Batch: Choosing the Right Data Pipeline Architecture
Understand when to use batch processing, real-time streaming, or a hybrid approach — with architecture diagrams, working code for each pattern, and a decision framework.
Secrets, Keys, and Tokens: Securing Your Python Automation Scripts
Stop hardcoding API keys in your scripts. Learn how to manage secrets properly with environment variables, vaults, token rotation, and secure CI/CD pipelines.