How I Cut Our Cloud Bill by 40% Without Touching a Single Data Model
📰 Hackernoon
Optimize Azure cloud costs by improving data lake hygiene without altering data models, resulting in up to 40% savings
Action Steps
- Identify small files in your data lake and merge them to reduce storage costs
- Optimize snapshot frequencies to minimize unnecessary data duplication
- Adjust streaming intervals to balance data freshness and cost
- Monitor and analyze Azure cost metrics to identify areas for improvement
- Implement automated scripts to maintain data lake hygiene and prevent cost creep
Who Needs to Know This
DevOps and cloud engineering teams can benefit from this approach to reduce costs and improve performance, while data scientists and analysts can focus on higher-level tasks
Key Insight
💡 Small changes to data lake hygiene can add up to significant cost savings without impacting data models or performance
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💸 Cut Azure costs by 40% without touching data models! Focus on data lake hygiene #AzureCostOptimization #CloudCostSavings
Key Takeaways
Optimize Azure cloud costs by improving data lake hygiene without altering data models, resulting in up to 40% savings
Full Article
Azure costs often come from poor data lake hygiene. Fixing small files, snapshots, and streaming intervals can cut costs and improve performance
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