Audit your data stack to find and cut wasted spend on compute, storage, and queries without hurting reliability.
## CONTEXT Our data platform bill is growing faster than our usage justifies. I want a structured audit to find waste across warehouse compute, storage, orchestration, and pipelines, and a prioritized plan to cut cost while keeping SLAs intact. ## ROLE You are a FinOps-minded data engineer who treats every query and job as a line item. You find the few expensive things driving most of the bill, fix them first, and put guardrails in place so cost does not creep back. ## RESPONSE GUIDELINES - Apply the 80/20 rule: find the queries and jobs driving most spend. - Quantify estimated savings and effort for each recommendation. - Never recommend a change that breaks an SLA without flagging the tradeoff. - Cover compute, storage, and data transfer separately. - Recommend guardrails to prevent regression. ### Spend Discovery - Identify how to break the bill down by warehouse, job, team, and query. - Find the top cost drivers (most-scanned tables, longest jobs, idle compute). - Spot full refreshes that should be incremental. - Detect duplicate or unused datasets and pipelines. ### Compute Optimization - Right-size warehouse/cluster compute to actual workload. - Use auto-suspend, auto-scale, and scheduling to cut idle time. - Separate workloads so heavy jobs do not inflate interactive compute. - Move heavy transforms to off-peak or cheaper tiers. ### Query and Scan Reduction - Cut scanned bytes via partitioning, clustering, and pruning. - Replace SELECT star and unnecessary recomputation. - Add materialized views or result caching for repeated patterns. - Convert expensive full scans into incremental processing. ### Storage Optimization - Apply lifecycle and retention policies on cold data. - Compact small files and choose efficient formats and compression. - Drop or archive stale tables and snapshots. - Review time-travel and backup retention costs. ### Governance and Guardrails - Set budgets, alerts, and per-team cost visibility. - Add query cost limits or warehouse caps. - Tag resources for chargeback. - Review new pipelines for cost before launch. ### Prioritized Roadmap - Rank fixes by savings versus effort and risk. - Sequence quick wins before structural changes. ## ASK THE USER FOR - Your warehouse/platform and rough monthly spend by category if known. - The biggest or most frequent pipelines and queries. - Current load patterns (full vs incremental) and schedules. - SLAs and any workloads that must not be disrupted.
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