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Strategies to Optimize Snowflake Cost
Reducing Cost and Improving Performance in Snowflake
Introduction
Overview of the importance of optimizing Snowflake cost
Introduction to the speakers and their expertise
Agenda for the presentation
Highlighting key accomplishments in reducing cost
Snowflake Deployment at Insta
Overview of Snowflake deployment at Insta
Number of users and warehouses
Queries per month and data usage
Access control settings for data security
Accomplishments and Cost Reduction
Summary of cost reduction achievements
Reducing storage cost by 33%
Optimizing query runtime and performance
Example of query runtime reduction
Observe, Analyze, and Optimize
Importance of observation and analysis for cost optimization
Query profiling and metrics
Query fingerprinting and tagging
Accountability and ownership
Analyzing Query Profile
Understanding query profile for optimization
Identifying expensive nodes and aggregates
Optimizing table scans through filtering and clustering
Monitoring caching and spilling
Optimizing Warehouse Size
Determining optimal warehouse size
Factors to consider for scaling
Importance of minimizing byte scan
Balance between vertical and horizontal scaling
Storage and Cloning Optimization
Maximizing storage efficiency
Using transient and temporary tables
Optimizing time travel and cloning
Monitoring and managing retained by clone bytes
Conclusion
Summarizing key learnings and takeaways
Importance of early cost detection and optimization
Role of accountable individuals in driving optimization
Appreciation for the audience's time and attention
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