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blog

compact blog template

  • title ·
  • tl;dr (1–2 lines)
  • hypothesis (measurable)
  • method / architecture (diagram + tech list)
  • required artifacts (repo, run commands, sample data)
  • results (2–3 numeric metrics)
  • lessons & trade-offs (3 bullets)
  • follow-ups & repo link

publication checklist

  • repo with run.sh / docker-compose ✔
  • architecture diagram (png/svg) ✔
  • one-page metrics report (md/csv) ✔
  • 3–5 code snippets + key files in repo ✔
  • seo tags & 3 keywords ✔
  • publish date, read-time, difficulty tag ✔
  1. cleaning the real world: reproducible etl with tests — mini — hypothesis: tests + docker reproduce clean load; metric: 100% tests pass on fresh env.
  2. from api to analytics: idempotent ingestion patterns — mini — hypothesis: idempotency avoids duplicates; metric: 0 duplicate rows after 10 replays.
  3. designing data lake zones: cost and partitioning trade-offs — intermediate — hypothesis: proper partitioning halves query scan bytes; metric: % scan-bytes reduction.
  4. airflow in production: retries, backfills and testing — intermediate — hypothesis: robust dag reduces manual interventions; metric: increase in successful completion rate after retries.
  5. building a realtime fraud detector: sliding windows and stateful processing — advanced — hypothesis: windowed aggregation detects anomalies within sla; metric: p95 latency and detection precision.
  6. cdc for analytics: schema evolution without downtime — advanced — hypothesis: cdc + idempotent upserts keep analytic view consistent; metric: consistency rate after mixed ops.
  7. feature stores demystified: offline-online consistency — expert — hypothesis: parity checks <1% mismatch; metric: offline-online mismatch %.
  8. starting a data mesh: governance, contracts, and small experiments — expert — hypothesis: domain contracts reduce integration failures; metric: contract-violation detections prevented.

for further endeavour proceed to appendix page