Author name: Abhay

Week 2 took you deep into the compute and storage layers — virtual warehouses, multi-cluster scaling, micro-partitions, table types, and view types. This practice test has 20 exam-style questions covering Days 7–12. Aim for 80% (16/20) before moving on. If you’re scoring below that, revisit the specific day’s post for the topics you’re missing. 01 […]

You’ve just wrapped up your first week — Snowflake’s architecture, editions, interfaces, and object hierarchy. That’s the foundation everything else builds on, and Domain 1 alone is 31% of the COF-C03 exam. Below are 20 exam-style questions that test whether you actually get these concepts or just read about them. Aim for 80% (16/20). If

Domain 4 is done. Over the last nine days (Days 31–38), you covered Query Profile, ACCOUNT_USAGE views, three types of caching, Query Acceleration Service, Search Optimization Service, clustering keys, materialized views, workload management, semi-structured data (VARIANT, FLATTEN, dot notation), and window functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG, NTILE, QUALIFY). That’s a massive amount of ground

Yesterday you learned how Snowflake handles semi-structured data — VARIANT, dot notation, casting with ::, and the all-important LATERAL FLATTEN pattern for exploding arrays into rows. Today we shift from data formats to data computation: window functions and aggregate functions. These are the SQL workhorses behind rankings, running totals, row comparisons, and grouped summaries. And

Yesterday you learned how to isolate workloads across warehouses, scale up vs. scale out, and diagnose queuing — all at the compute layer. Today we shift to a topic that Snowflake handles better than almost any other data warehouse: semi-structured data. JSON from APIs, Avro from Kafka, Parquet from data lakes — Snowflake ingests all