Stop Feeding Snowflake Junk:
How to Cut Storage Costs 20-40% Without Breaking a Single Query

Snowflake is on an incredible run. With a strong product and AI tailwinds, Snowflake is like the Ferrari of the modern data stack, blazing fast, elegantly designed, and built to scale.

Enterprises lean on it for everything from analytics to machine learning because it just works. With consumption-based pricing, separation of storage and compute, and near-infinite elasticity, Snowflake helped to rewrite the rules of cloud data warehousing.

But there’s an important catch for IT teams: even Ferraris need a pit crew.

Without lifecycle discipline, Snowflake often ends up idling in the driveway, guzzling premium data for no reason. The result? Skyrocketing storage bills, stale datasets clogging pipelines, and compliance teams staring down risk they didn’t even know existed.

The uncomfortable truth is this: Snowflake isn’t focused on solving for messy pipelines, metadata sprawl, or dark data. It simply makes whatever you put into it, good or bad, fast. And that means organizations that don’t actively manage data lifecycles end up paying more for less.

That’s where Pentaho Data Optimizer (PDO) comes in. PDO is the pit crew Snowflake never knew it needed: always in the background, keeping your environment lean, compliant, and cost-efficient.

The Snowflake Cost Mirage

Elasticity is Snowflake’s superpower – and also its Achilles’ heel. Scaling up is as easy as clicking a button. Scaling down? Not so much.

Most organizations don’t realize how much of their Snowflake bill is driven by data that hasn’t been touched in months or even years. “Cold” data sits in premium-priced storage tiers, consuming budget without providing value. And unlike compute, which you can scale down quickly, storage costs accumulate silently month after month.

Common culprits include:

• Massive staging tables that were never cleaned up
• Old project data no one remembers creating
• Orphaned snapshots from dev and test environments
• Historical logs quietly piling up for years

Individually, these don’t seem like much. But in aggregate, they balloon into a six or even seven-figure line item.

Zombie Tables and Dark Data

Ask most Snowflake teams where their storage costs are coming from, and you’ll get guesses, not answers. Snowflake’s billing doesn’t break down ownership, usage frequency, or freshness. That makes it nearly impossible to run chargebacks or hold teams accountable.

Meanwhile, compliance leaders have a different nightmare: dark data. Industry estimates suggest that 40-90% of enterprise data is “dark,” meaning it is collected, stored, and paid for but remains unused and ungoverned. This is both a cost problem and a risk problem. Old datasets may contain PII or sensitive information, and without visibility or retention enforcement, those risks grow unchecked.

The result is a double hit: runaway costs and regulatory exposure.

Optimize Savings, Compliance, and Performance – Together

Pentaho Data Optimizer (PDO) was built for exactly this challenge. It’s Snowflake-native but cloud agnostic, designed to work across hybrid and multi-cloud environments. Think of it as a clean-up crew, cost watchdog, and automation engine rolled into one.

• Scan your Snowflake environment and automatically classifies tables by usage, freshness, and lineage
• Identify stale, low-value, or orphaned data that no one is accessing
• Tier cold data to low-cost object storage like AWS S3, Google Cloud Storage, or on-prem, while preserving access via metadata pointers
• Tag ownership and usage to enable chargebacks and accountability
• Automate retention policies and enforce governance without manual scripts
• Surface risks like orphaned PII or forgotten dev environments
• And since PDO requires no rip and replace, there are no disruptive migrations, and no changes to existing queries.

PDO makes Snowflake leaner, cost-effective, and safer – without breaking queries or dashboards.

Real-world examples in action:

• One enterprise reduced storage by 30% while actually improving query speed, since their Snowflake environment wasn’t bogged down by unnecessary cold data.
• Both compliance teams now have retention policies enforced automatically, reducing audit stress and cutting governance costs.

These aren’t hypothetical – they’re quick wins that teams can achieve in weeks, bringing benefits to every stakeholder.

• FinOps Leaders / CFOs finally get transparency into where storage dollars are going, enabling chargebacks and predictable budgeting.
• VPs of Data Engineering free their teams from 2 AM cleanup scripts and firefighting, letting engineers focus on higher-value work.
• Cloud Architects get lifecycle automation and hybrid flexibility without duct-tape scripting.
• And CDOs / Compliance Officers gain confidence that retention policies are enforced and risk is reduced, all while cutting costs.

Stop Feeding Snowflake Junk Data

Snowflake is brilliant at what it does – but it won’t clean up your mess for you. Without lifecycle automation, every organization eventually ends up feeding Snowflake junk: cold data, zombie tables, forgotten snapshots, and dark datasets that bloat costs and increase risk.

Pentaho Data Optimizer is the pit crew that makes sure your Ferrari runs at peak performance – keeping costs lean, governance tight, and pipelines clear.

If your Snowflake bill is getting heavy, maybe it’s time for a pit stop.

Run your numbers with the PDO ROI calculator.