There is a moment in every Snowflake deployment when the data estate crosses a line. Not a technical limit. An organizational one.
Somebody creates a table that nobody uses. Then a connector starts refreshing it daily. Then someone clones the schema for testing and forgets about it. A year later, you have thousands of objects across hundreds of schemas. Some are critical. Some haven’t been touched in months/years. Some are being refreshed every four hours by an ETL/ELT connector that nobody remembers setting up.
The cost isn’t just storage. It’s the operational drag. When someone decides to turn off a pipeline, the question isn’t whether to do it. It’s who uses the tables that it refreshes. And answering that question, across schemas, teams, and months of access history, takes days. Sometimes weeks.
We’ve seen this pattern in every enterprise Snowflake deployment we’ve worked with over the past 18 years of data platform engagements. The scale changes, but the problem doesn’t.
Introducing GrowthArc’s Data Estate Intelligence
Data Estate Intelligence is a Snowflake Native App, now available for free on the Snowflake Marketplace for a 30-day free trial that gives you instant visibility into your entire data estate.
Install it in five minutes. Select a database. Within seconds, every table and view is classified by lifecycle status based on actual access history:
- Active: accessed within the last 7 days
- Stale: last accessed 8 to 30 days ago
- At Risk: last accessed 31 to 90 days ago
- Unused: last accessed over 90 days ago
- Never Used: no recorded access since creation
You see who accessed what, when they last touched it, and whether they read or wrote. There is a health score for every schema. You see the estimated monthly storage cost of every unused object. And you see zombie pipelines, tables that a connector is actively refreshing, but nobody ever reads from.
The Pipeline Decommission Problem, Solved
This is the feature that started the whole project.
You’re turning off an ETL/ELT connector, or deprecating a DBT model, or consolidating schemas after a migration. Before you flip the switch, you need to know: which tables does this pipeline touch? Who uses them? When was the last access? Is it safe?
In Data Estate Intelligence, select a schema or paste table names from your connector config. The app instantly returns every affected user, their last access date, read vs write activity, and a decommission readiness score:
- Safe: no access in 90+ days, two or fewer users, no recent writes
- Caution: no access in 30+ days, three or fewer users. Low risk, but verify first.
- Blocked: recently accessed by multiple active users. Do not decommission without stakeholder sign-off.
Download the report as Excel or CSV. Attach it to an email. The two-week audit cycle becomes a two-minute search.
Find Any Table Across Every Schema and Database
One of the first requests from a client with Tons of tables: they had identically named tables in dozens of schemas. DIM_CUSTOMER in RAW, STAGING, ANALYTICS, MARKETING, and eleven other schemas. No way to compare them without checking each schema individually.
The Object Search tab solves this. Type a table name, and the app finds every instance across all schemas, or toggle to search across all databases in your account. Each result shows its full lifecycle status, access history, users, storage, and decommission readiness.
When duplicates are found, the app automatically recommends which copy to keep based on actual usage patterns: who accesses it, how often, and how recently. The rest are candidates for consolidation or removal.
Built for Enterprise Scale
We deployed the initial version at a client running tons of tables with millions of access records. So, we rebuilt the data pipeline from the ground up. The app pushes all heavy aggregation into Snowflake SQL. Instead of pulling all the raw rows into Python for processing, it aggregates inside Snowflake and returns one summary row per object. Tabs load data on demand; only the Dashboard queries run at startup. The result: a full analysis of all the tables loads in under two minutes.
A bigger warehouse doesn’t fix a bad data pipeline. Architecture does. That’s the same principle we apply to every client engagement.
What’s Included
The app runs entirely inside your Snowflake account. No external dependencies. No data leaves your environment. Completely read-only. Seven tabs:
- Dashboard: KPIs, lifecycle status distribution, schema health scores, zombie pipeline detection.
- Inventory: full object catalog with filters and an object inspector showing users, dependencies, and lifecycle details.
- Object Search: cross-schema and cross-database search with duplicate detection.
- Pipeline Impact: decommission analysis with user impact and readiness scoring.
- Access Intel: filter access history by user or object, trends over time, per-object summaries.
- AI Assistant: ask natural language questions about your data estate, powered by Snowflake Cortex.
- Export: six-sheet Excel report with SQL cleanup scripts and estimated cost savings.
Try it – The App is free for the first 30 days
GrowthArc’s Data Estate Intelligence is live on the Snowflake Marketplace. Free to install. No credit card or setup calls. Five minutes from Marketplace to your first data estate analysis.
Search for “GrowthArc Data Estate Intelligence” on the Snowflake Marketplace.
If you’re dealing with table sprawl, unused objects, or the pipeline decommission problem at scale, we’d like to hear about it. Book your Enterprise AI Strategy call with our experts.
