> Wibbling

Author name: Abhay Krishnan

With over five years of data engineering experience at EY and Infosys, Abhay Krishnan specializes in building scalable data pipelines and cloud warehousing solutions. He is a certified SnowPro Core professional, alongside credentials in AWS and Azure. Abhay created this 50-day track to solve a problem he faced firsthand: the lack of a structured, free resource for Snowflake certification prep. Follow him on LinkedIn for more data engineering insights.

Day 39: Clustering Keys & Materialized Views for Snowflake Performance

Day 38 added two serverless levers that left the warehouse alone. One offloaded a heavy scan. One built a search access path for point lookups. Today’s two tools change the data itself. A clustering key reorders rows so a query scans fewer micro-partitions. A materialized view stores a precomputed result so a repeated query skips

Day 39: Clustering Keys & Materialized Views for Snowflake Performance Read More »

Day 38: Query Acceleration Service & Search Optimization in Snowflake

Day 37 put each workload on its own warehouse. It also weighed scaling up against scaling out. Those levers change the warehouse itself. Today’s two levers leave the warehouse unchanged. They add serverless help on top of it. The Query Acceleration Service sends heavy scan work to a shared serverless pool. Search Optimization builds a

Day 38: Query Acceleration Service & Search Optimization in Snowflake Read More »

Day 37: Snowflake Workload Management & ACCOUNT_USAGE Performance Views

Day 36 taught you to read a single query’s profile. Today you zoom out to the warehouse that runs all of them. The job is to put the right work on the right warehouse, then read the columns that show when a warehouse is overloaded. One trap repeats across Domain 4: when concurrency is the

Day 37: Snowflake Workload Management & ACCOUNT_USAGE Performance Views Read More »