The Scenario
The CTO meeting is in two hours. You're the BI lead. Someone in last week's cloud cost review asked how much storage your ANALYTICS.REPORTING schema is actually consuming, and nobody had a clean answer. Your CTO followed up this morning: get me a full table inventory — all 120 tables, row counts, byte sizes — before the sync.
You know where the data lives. You've run SHOW TABLES IN SCHEMA ANALYTICS.REPORTING before. What you haven't done is turn that output into a formatted, sorted Google Sheet that a CTO can read in a two-hour window.
The bad version:
- Run SHOW TABLES IN SCHEMA ANALYTICS.REPORTING in SnowSight
- Export the result — which includes 20 columns you don't need, in an order nobody asked for
- Paste into a Google Sheet, delete the irrelevant columns, rename the three you're keeping, sort by size descending
- Realize the byte sizes are in scientific notation and you need to convert them to readable numbers
You have two hours. You've used forty minutes.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, connects to Snowflake through its built-in integration, and can pull a targeted schema-level table inventory — structured, sorted, and labeled exactly as you need it.
Open a blank Google Sheet and paste this into the SheetXAI sidebar:
List all tables in Snowflake database ANALYTICS schema REPORTING and write each table's name, row_count, and size_bytes into columns A, B, and C of this sheet — sort by size_bytes descending
What You Get
- Column A: table_name
- Column B: row_count
- Column C: size_bytes, sorted descending
- 120 rows if your schema has 120 tables — no pagination, no manual export, no column cleanup
- Header row in row 1
What If the Data Is Not Quite Ready
You need size in gigabytes rather than bytes
List all tables in Snowflake database ANALYTICS schema REPORTING, write table_name into column A, row_count into column B, and size in gigabytes (rounded to 2 decimal places) into column C — sort by column C descending with headers in row 1
You need tables from multiple schemas in one sheet
List all tables in Snowflake database ANALYTICS for schemas REPORTING and PUBLIC, write schema, table_name, row_count, and size_bytes into columns A through D — sort by size_bytes descending with headers in row 1
Filter to tables created in the last 90 days
Show all tables in Snowflake database ANALYTICS schema REPORTING that were created in the last 90 days, write table_name, row_count, size_bytes, and created_date into columns A through D — sort by created_date descending
Full inventory with a cost-attribution column based on size tiers
List all tables in Snowflake database ANALYTICS schema REPORTING, write table_name, row_count, and size_bytes into columns A, B, C — then add a column D called size_tier with values: LARGE if size_bytes > 10000000000, MEDIUM if between 1000000000 and 10000000000, SMALL otherwise — sort by size_bytes descending
The pattern: the formatting, the sort order, and any derived columns are part of the same prompt as the data retrieval.
Try It
Get the 7-day free trial of SheetXAI and open a blank Google Sheet, then ask it to pull a targeted table inventory for any Snowflake schema — with whatever columns, sorting, and derived fields your audience needs. For the full account-wide version, see build a Snowflake data catalog, or return to the Snowflake integration overview.