Analytics the Business Actually Trusts
from $40K. 4 to 6 weeks.
from $200K. 2 to 4 months.
from $15K per month.
Where Do You Start?
Two situations we see most often. Most enterprises in this space are modernizing, not greenfielding.
Your Dashboards Exist but Nobody Trusts Them
You have a data warehouse. You have BI tools. You have dashboards. Three teams calculate the same metric three different ways. Executives quietly distrust the numbers. Your data team spends 70 percent of its time reconciling instead of analyzing. The fix isn't more tools. It's a defensible semantic layer underneath everything.
Analytics Architecture Review (4 to 8 weeks, from $40K). Then Analytics Modernization Program (2 to 4 months, $200K to $280K typical).
Production lakehouse on your existing cloud or platform investment. Rebuilt semantic layer with versioned, owner-attributed metrics. Redesigned executive and operational dashboards. Embedded enablement so your team owns it after delivery.
You Modernized. Now You Need Ongoing Capacity
Your modernization is complete or in motion. The semantic layer exists. The dashboards work. Now business teams keep asking for new metrics, new dashboards, and new pipelines faster than your data team can deliver. You don't need another vendor. You need embedded capacity.
Analytics-as-a-Service Retainer (12 months rolling, from $15K per month).
Dedicated analytics engineering capacity. New metric and dashboard delivery on monthly cadence. Pipeline reliability monitoring. Quarterly governance review with named owners.
What a Typical Engagement Looks Like
Most clients arrive in the Modernize situation. The shape of a typical Architecture Review plus Modernization Program is below. Analytics-as-a-Service runs as monthly cadence after delivery completes.
Analytics Architecture Review
- Weeks 1 to 2: Current-state estate audit. Sources, pipelines, semantic gaps, governance maturity, tooling fit assessment.
- Weeks 3 to 4: Duplication and reconciliation map. Metric ownership proposed with named business stakeholders.
- Weeks 5 to 6: Target-state architecture. Modernization roadmap. Tooling recommendations (Tableau, Power BI, Looker, Superset). SOW for the modernization program.
Analytics Modernization Program
- Weeks 7 to 9: Lakehouse foundation on your cloud or platform investment. Production ingestion. Data quality monitoring.
- Weeks 10 to 13: Semantic layer build. Versioned metric definitions. Owner attribution. Governance model.
- Weeks 14 to 17: Executive and operational dashboards rebuilt. Embedded enablement sessions for your data team.
- Week 18: Handover documentation. Working session with your team.
Hypercare and Handover
- Senior engineers on call. Pipeline reliability monitoring. Metric definition review with named owners.
- Operations runbook finalized.
Analytics-as-a-Service Retainer
- Dedicated analytics engineering capacity.
- New metric and dashboard delivery against your team's backlog.
- Pipeline reliability monitoring.
- Quarterly governance review.
Typical first-year program investment: Architecture Review, Modernization, plus first year of Analytics-as-a-Service is $380K to $500K. Most clients see reconciliation time drop from days to hours within the first quarter post-modernization.
Modernizing the semantic layer your AI strategy will run on?
Who's on the Team
The senior practitioner who scopes the work is the senior practitioner who delivers it. Your team is named in the SOW.
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Lead Architect, Analytics & Data
12+ years in lakehouse architecture and semantic-layer design. Owns the architecture and the metric ownership model.
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Senior Engineer, Lakehouse & Pipelines
Deep on Iceberg, Delta Lake, Spark, dbt, Airflow. Writes the production data infrastructure.
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Senior Engineer, Semantic Layer & BI
Owns metric definitions, BI tool integration (Tableau, Power BI, Looker, Superset), and dashboard rebuild.
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Platform Engineer
Cloud-agnostic deployment, infrastructure-as-code, observability.
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Delivery Lead
Sprint cadence, fortnightly executive steering, RAID log.
How We Approach the Work
The semantic layer is the work. The gap between "we have data" and "we have trusted analytics" is rarely a tooling problem. It is a semantic, governance, and ground-truth problem. We rebuild the middle layer first, before touching the BI layer above it.
Metrics get named owners. Every metric in the semantic layer is attributed to a named business owner. When the metric changes, the owner approves. When a dispute arises about how a number is calculated, there is a single canonical answer. This is the change that makes dashboards land.
We work across BI tools, not against them. Tableau, Power BI, Looker, Superset. We work with what your team has chosen and the semantic layer underneath does the real work. We don't recommend tool migration unless the existing tool genuinely fails the requirement.
Open source first where it's the right call. Iceberg, Delta Lake, dbt, Airflow. Production-grade open-source data infrastructure where it fits. Databricks or Snowflake when you've already invested or the platform earns its place. Either way, the architecture is yours and exit cost is managed.
Technology and Platform Posture
You have already chosen your platforms. We deliver against your existing footprint. Below is what we work with most often.
Lakehouse and Data Platforms
Apache Iceberg 
Delta Lake 
Databricks 
Snowflake Cloud-native lakehouses on AWS, Azure, GCP.
Semantic Layer and Pipelines
dbt 
Airflow 
Dagster 
Atlan Collibra (where pre-invested). Custom semantic layer where the use case warrants.
BI and Visualization
Tableau 
Power BI 
Looker 
Superset Metabase. We deliver dashboards on whatever your team uses today.
Cloud-agnostic by architectural decision, not by inheritance.
Bring the estate. We return with target architecture, scope, and roadmap.
What to Expect from an Analytics Modernization
Modernizations typically deliver in the following ranges. Specific outcome targets are scoped during the Architecture Review and written into the SOW.
from days to hours within first quarter post-modernization.
90 percent plus at handover.
70 to 85 percent within 60 days.
Where a target falls outside range due to constraints in your existing estate or governance posture, we surface that during the Architecture Review and scope to a defensible number. We do not commit to outcomes we cannot defend.
From the Analytics Practice
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A week-by-week runbook for the first 90 days of a FinOps engagement. Quick wins, governance, and operating model rollout. Written as a runbook, not as marketing copy.
Scope an analytics engagement
Scope an Analytics Engagement
Tell us where you are. Modernizing or operating. Thirty minutes is enough to know if there's a fit and what shape the engagement would take.
If we're not the right firm for what you need, we'll point you to who is.