Dashboards take 30+ seconds to load.
Users complain, adoption drops, and executives quietly stop trusting the data.
Data & Analytics · Looker performance
Looker performance optimization — fix slow dashboards and the BigQuery bill behind them
Slow dashboards are never random. There is always a specific set of queries, PDTs, and LookML patterns causing them — and they are usually the same ones inflating your BigQuery bill. We find them, fix them, and measure the difference on your own billing.
40%+ faster dashboards 30%+ lower BigQuery cost First results in 6–8 weeks
The tension · 01
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Sound familiar?
These are the patterns we see week after week in enterprise Looker environments.
PDTs take hours to build.
Data freshness slips, and morning dashboards show yesterday's numbers.
The LookML grew without an owner.
Duplicated Explores, unused views, no conventions — technical debt slowing everything down.
The BigQuery bill keeps climbing.
Unoptimized queries scanning terabytes, no slot strategy, no alerts when a query misbehaves.
Nobody can see the problem.
No performance monitoring, no cost attribution. Issues surface only when someone complains.
If any of these landed: the slow dashboard and the expensive bill are almost always the same problem, seen from two sides.
The method · 02
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Four steps, measured against your baseline.
Performance audit
We analyze System Activity, query logs, and LookML structure. Output: the exact queries, PDTs, and Explores causing slowness and overspend, in one shared document.
Week 1Quick wins
Cache tuning, aggregate awareness, PDT scheduling, and the obvious expensive queries. You see improvement before any deep refactor.
Weeks 1–2Deep optimization
LookML refactored to incremental PDTs, BigQuery partitioning and clustering, Explore consolidation, SQL rewrites. This is where the biggest gains live.
Weeks 2–6Monitoring & handoff
Performance dashboards, alerts in Slack or Teams, documentation, and training. Your team keeps visibility — and the skills to maintain it.
Weeks 6–8What we don't do: rebuild your stack from scratch. We optimize what you have, on your infrastructure.
What we optimize · 03
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Deep work across the whole Looker + BigQuery stack.
LookML architecture
Views, Explores, model structure. Refactored for performance, maintainability, and scale.
PDT strategy
Incremental PDTs, materialized views, shared caching. The right persistence layer for each use case.
Query optimization
SQL rewrites, aggregate awareness, elimination of n+1 patterns and unnecessary joins.
BigQuery tuning
Partitioning, clustering, slot management, BI Engine. The warehouse tuned for Looker workloads.
Performance monitoring
System Activity dashboards, custom alerts, cost tracking per query, user, and dashboard.
Governance & standards
Naming conventions, content validation, development flow. So the fix stays fixed.
Pricing · 04
The cost of slow, before the cost of fixing it.
A misconfigured Explore can silently cost thousands per month in BigQuery — with zero alerts. Our optimization work has produced 40%+ faster dashboards and 30–60% lower BigQuery costs, measured on the client's own billing. That's the number the audit puts in front of you first.
Free Looker audit
Read-only. We name the queries and Explores costing you the most. No findings, no charge.
$0 · 15 min
Performance audit (scoped)
Full performance review: queries, PDTs, LookML, BigQuery. Prioritized fix plan with estimated impact per finding.
Fixed scope · 1 week
Fractional Looker expert
Ongoing optimization, monitoring, and development embedded in your team.
Monthly retainer · flexible scope
Larger optimization projects are scoped after the audit — fixed price, committed outcomes in the SOW.
The proof · 05
Measured on the client's billing, not on a slide.
Deep tuning of a high-volume Looker and BigQuery platform: 40%+ faster dashboards, 30%+ lower BigQuery cost, 3x more self-service. What we didn't do: migrate the warehouse or rebuild the model from scratch.
FAQ · 06
What prospects usually ask before the first call.
Why are my Looker dashboards slow?
Four patterns explain most slow Looker dashboards: queries scanning unpartitioned tables, PDTs rebuilt more often than needed (or too big to build fast), Explores with too many joins for the question being asked, and missing aggregate awareness forcing detail-level scans. The audit tells you which combination applies to your instance — it's rarely all four, and it's almost never "Looker is just slow."
How much does Looker performance optimization cost?
It depends on scope. The free 15-minute audit costs nothing and names your biggest offenders. From there you get a fixed-scope proposal: a one-week performance audit, a full optimization project (typically 2–6 weeks depending on complexity), or ongoing support. Book the free audit and we'll scope it — you'll know the cost before any work starts.
How long until we see results?
Quick wins — cache tuning, obvious query fixes, PDT scheduling — are visible in the first two weeks. Deep optimization lands its full impact within 6 to 8 weeks, measured against your baseline billing and load times. That timeline goes into the SOW as a commitment, not an estimate.
Will optimization break our existing dashboards?
No. We use Looker's Content Validator extensively, test every change in development mode, and deploy with rollback plans. Your dashboards keep working — they just load faster. Data reconciliation confirms the numbers stay identical.
Do you need access to our production instance?
Developer or Admin access lets us read System Activity and query logs — the raw material of the audit. We work in development mode first, follow your change-management process, and request the minimum permissions needed. Read-only is enough for the free audit.
Can you also reduce our BigQuery costs?
Yes — in practice it's the same work. The queries that make dashboards slow are usually the queries inflating the bill. Our engagements measure both: load times against your baseline, and cost against your actual BigQuery billing. If cost is your primary pain, see our BigQuery cost optimization service.
What if we don't have BigQuery expertise in-house?
That's the most common situation. We handle the warehouse side — partitioning, clustering, slots, BI Engine — and leave documentation and training behind so your team can maintain it. You don't need a FinOps hire to keep the savings.
Let's talk · 08
Find out what's actually slowing you down.
Fifteen minutes, read-only. We name the queries and Explores behind your slow dashboards — and what fixing them is worth on your BigQuery bill.
Related services · 07
More ways we work on Looker and BigQuery.
LookML development, embedded analytics, dashboards, and team training — knowledge your team keeps.
Partitioning, slot strategy, query tuning, and FinOps monitoring — measured on your own billing.
Migrate to Looker from Tableau or Power BI
Zero-downtime BI migrations: parallel run, validated data, trained team, fallback plan.