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Service Area

Analytics &
Business Intelligence

Dashboards that nobody looks at are expensive decorations. We build analytics capabilities your business leaders actually use to make faster, more confident decisions — with data they trust.

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The Challenge

The real analytics problem isn't the tool — it's the trust

Most companies have a BI tool. Many have multiple. And yet, the most common thing we hear from executives is still: "I don't trust the data." Or "Every team's numbers are different." Or "By the time the report is ready, the decision has already been made."

The root cause is almost never the dashboard itself. It's the layer underneath — inconsistent definitions, undocumented business logic, no clear ownership, and a transformation layer that nobody fully understands.

We fix that first. Then we build the dashboards and reporting capabilities that sit on top. The result is analytics that earns trust — and actually changes how people in your organization make decisions.

41%
of business leaders say they regularly make decisions without the data they need to be confident
3x
faster average reporting cycle after implementing a proper semantic / metrics layer
< 8 wk
typical time to deliver a production-ready executive dashboard suite from a clean data foundation

Types of Projects

What an Analytics & BI engagement looks like

We meet you where you are. Whether you're starting from zero or fixing a broken reporting environment, here's how we typically scope the work.

📈
Build

Executive Dashboard Suite

A curated set of high-level dashboards built for C-suite and VP-level decision-making. Focused on the metrics that actually drive the business — revenue, margins, retention, pipeline — presented clearly, refreshed reliably, and trusted by everyone who sees them.

What you get
  • 3–5 core executive dashboards with agreed-upon definitions
  • Automated refresh with alerting on stale data
  • Drill-through capability to operational detail
  • Documented metric logic for auditability
🧩
Platform

Self-Serve Analytics Build-Out

Reduce the analytics team's ticket backlog by giving business users the ability to answer their own questions. We design the semantic layer, access model, and training that makes self-serve actually work — without analysts spending every day fixing what people break.

What you get
  • Governed semantic layer with business-friendly field names
  • Role-based access and row-level security model
  • User training and self-service playbook
  • Measured reduction in ad-hoc analytics requests
📐
Foundation

Metrics Layer Implementation

Establish a single, centralized definition of every metric your business cares about. Using tools like dbt Metrics, Cube, or LookML, we create a source-of-truth layer that ensures everyone — across every tool and every team — is calculating revenue, churn, and conversion the same way.

What you get
  • Documented metric catalog with business definitions and owners
  • Semantic layer integrated with your existing BI tools
  • Eliminated metric discrepancies across reports
  • Framework for adding new metrics with consistency
Quality

Data Quality & Trust Program

If your stakeholders don't trust the data, no dashboard will help. We design and implement a data quality framework — automated tests, anomaly detection, SLA monitoring, and a clear process for investigating and resolving data issues before they reach the business.

What you get
  • Automated data quality tests across critical pipelines
  • Anomaly detection with stakeholder alerting
  • Data SLA framework with ownership and escalation paths
  • Measurable improvement in data trust scores
🔄
Migration

BI Tool Migration

Moving from Tableau to Power BI, from Looker to Metabase, or consolidating multiple tools into one? We plan and execute BI migrations that preserve your existing logic, eliminate duplicate reports, and leave you with a cleaner, more maintainable environment than you started with.

What you get
  • Content audit and rationalization (kill the dashboards nobody uses)
  • Migrated reports with validated parity to originals
  • Governance model for the new environment
  • Team training on new tooling
🏛️
Program

Analytics Center of Excellence

For organizations that want to build a durable internal analytics capability — not just projects. We help define the operating model, standards, and processes for an Analytics Center of Excellence: how work gets prioritized, how quality is maintained, and how the function scales as the business grows.

What you get
  • Analytics operating model and RACI framework
  • Development standards, review processes, and naming conventions
  • Intake and prioritization model for analytics requests
  • Hiring profile and onboarding playbook for future team members

Tech Ecosystem

Tools & platforms we work with

We work across the leading BI and analytics platforms. Tool choice is always driven by your team, your use cases, and your budget.

BI & Visualization

Tableau Power BI Looker / LookML Metabase Sigma Lightdash Superset

Metrics & Semantic Layer

dbt Semantic Layer Cube.dev Metriql AtScale

Data Quality & Observability

dbt Tests Great Expectations Monte Carlo Soda Elementary

Engagement Models

How we structure this work

Scoped to your starting point and how fast you want to move.

Common Questions

What people ask before starting

Not unless you want to. Most of the time, the tool isn't the problem — it's what's feeding it. We work with whatever BI tool you're already using and focus on making it work better, not replacing it unnecessarily. If a migration makes sense, we'll tell you honestly — but we're not going to recommend a migration to justify our fees.
Dashboard sprawl is almost always a symptom of two things: stakeholders who can't find what they need (so they ask for more), and a semantic layer that's too technical for self-service. We fix both — clean up the existing environment, build a proper self-serve layer, and put a governance process in place so new dashboards go through a "do we actually need this" gate.
In practice: nobody debates the number in the meeting. Trust is achieved when the definition is documented and agreed upon, the calculation is transparent and testable, the data is known to be fresh, and there's a clear person to contact if something looks wrong. We design for all four of those conditions, not just the dashboard aesthetics.
That's actually the more common starting point. If your data foundation needs work before analytics will stick, we'll say so and help you sequence the work correctly — or take on both pieces together. Building beautiful dashboards on a broken foundation is a waste of everyone's time and money.

Related Services

Services that complement this work

Ready to build analytics your team actually trusts?

Let's have a conversation about your current environment and what it would take to fix it.