Data pipelines cost 2-5x what most organizations budget. Here's why.
Budget: compute + storage. Reality: compute + storage + data transfer + processing + monitoring + error handling + schema management + team time.
Optimization: batch where possible (real-time costs 3-5x more), compress data in transit (-30-50% transfer costs), implement data lifecycle policies (auto-archive after 90 days), and use columnar formats (Parquet: 75% storage reduction vs. CSV).
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11 minReal-time data processing costs 3-5x more than batch for most use cases.
8 minPoor data quality costs organizations $12.9M per year on average. Prevention costs 1%.
9 minPublished Work
This article expands on ideas from my published work in CIO.com, Built In, Mind the Product, and HackerNoon. View published articles →
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