The Problem

Data platform costs are notoriously difficult to attribute. Engineering teams move fast, cloud bills are opaque, and the gap between what you’re paying and what you actually need widens every quarter.

The result: most organizations are running at 150–200% of their true cost floor without knowing it. Storage accumulates unchecked. Queries run without optimization. Compute clusters idle between jobs. Each line item looks small in isolation — together, they compound into significant, recurring waste.

LakeAudit finds the waste, quantifies it, and gives you a clear path to eliminate it.

What We Audit

LakeAudit examines every cost-bearing layer of your data lake infrastructure:

• Object Storage: Orphaned datasets, duplicate tables, unpartitioned data, cold-tier candidates, and retention policies that no longer reflect reality. We map your full storage footprint and identify what’s earning its keep — and what isn’t.

  
  

• Query Patterns: Expensive, redundant, and unoptimized queries are one of the largest hidden cost drivers in data lakes. We analyze query history, identify full-table scans, missing partitions, and inefficient join patterns — and quantify the dollar impact of each.

  
  

• Compute & Cluster Utilization: Over-provisioned clusters, always-on workloads that should be on-demand, and jobs that could be restructured to reduce runtime. We evaluate your compute configuration against actual workload patterns and surface concrete rightsizing opportunities.

How It Works

• Stage 1 — Scope:  Align on your environment, platforms, and priorities before any work begins. Output: audit charter, data access checklist.

• Stage 2 — Diagnose:  Deep inspection across storage, queries, and compute layers. Output: raw findings across all three layers.

• Stage 3 — Quantify:  Attach dollar values to every identified waste pattern. Output: waste register with cost estimates.

• Stage 4 — Recommend:  Prioritize actions by effort-to-impact ratio. Output: prioritized action plan.

• Stage 5 — Implement:  Execute fixes directly or guide your team through each item. Output: realized savings, implementation notes.

• Stage 6 — Realize:  Verify that savings materialize and put guardrails in place to prevent regression. Output: cost baseline, monitoring setup.

The early stages are deliberately low-commitment — you’ll see concrete findings before any significant work begins.

What You Get

• Full waste register: Every identified cost leak, categorized by layer and quantified in dollars

• Prioritized action plan: Ranked by effort-to-savings ratio so your team knows exactly where to start

• Shovel-ready recommendations: Specific, actionable steps, not generic advice

• Cost baseline: A documented floor to measure against and defend going forward

• Regression guardrails: Monitoring and alerting configuration to prevent waste from creeping back

Who This Is For

LakeAudit is built for teams running Databricks, Snowflake, Apache Iceberg, or Spark-based architectures at scale — typically processing tens to hundreds of terabytes daily — where platform costs are visible in the budget but the levers to control them aren’t clear.

It’s particularly valuable when:

• Cloud costs are growing faster than data volume

• Your team doesn’t have dedicated FinOps or platform engineering capacity

• You’ve had cost spikes with no clear cause

• You’re preparing to negotiate a new cloud or platform contract and need a defensible cost baseline

What We Don't Do

We don’t deliver slide decks with generic recommendations and leave you to figure out the details. Every finding in LakeAudit is tied to a specific resource, a specific dollar amount, and a specific action. Implementation support is available if you need it — but the plan itself is designed to be handed to your team and executed without us in the room.

No long commitments required.  The audit is a contained, time-bounded engagement. You’ll have findings in hand before making any decision about ongoing work.

Get Started

The first step is a brief scoping call to confirm fit and establish data access. From there, most audits complete within two to three weeks.

If your data platform costs are growing and you don’t have a clear picture of why — or where to cut — LakeAudit is the fastest path to answers.

Contact us today to schedule a scoping call.