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Analytics & Business Intelligence

Dashboards and reports should change behavior, not just display numbers. We build BI systems that surface the metrics your teams actually need — then train them to use what we build.

Key Takeaways

Analytics and business intelligence (BI) transforms your raw data into dashboards, reports, and self-service tools that help every team make faster, better decisions. We implement BI platforms that reduce report-request bottlenecks and give leadership real-time visibility.

  • Executive dashboards that answer strategic questions in minutes, not days
  • Self-service analytics that reduces 'Can you pull this data?' requests by 80%
  • Platform-agnostic implementation across Power BI, Tableau, Domo, and others
  • Consistent metrics and definitions across departments
  • Training that ensures your team can maintain and extend dashboards independently

BI that changes how your organization operates

The goal of business intelligence isn't dashboards — it's better decisions made faster. A well-built BI system gives every level of the organization access to the data they need, in the format they'll actually use, updated at the cadence that matters.

We build BI systems that accomplish three things:

  • Dashboards that get used. We start with the decisions your team makes weekly and build from there. If a dashboard doesn't change someone's behavior, it's not doing its job.
  • Self-service that actually works. Business users can answer their own routine questions — filter, sort, drill down — without waiting for the data team to write a query.
  • One version of truth. Revenue means the same thing in every report. Metrics are governed, definitions are documented, and the numbers match across departments.

Analytics for every stage of maturity

Descriptive Analytics

What happened? Automated dashboards and reports that give your team a clear, consistent view of business performance — daily, weekly, or in real time. The foundation everything else builds on.

Diagnostic Analytics

Why did it happen? Drill-down capabilities and ad-hoc analysis that help you understand the drivers behind the numbers. When revenue drops or costs spike, you can trace it to the source.

Predictive Analytics

What will happen? Statistical models and machine learning that forecast trends, identify risks, and quantify opportunities before they materialize.

Prescriptive Analytics

What should we do? Decision-support systems that recommend specific actions based on data — optimizing pricing, staffing, inventory, or marketing spend.

Tool-agnostic, outcome-focused

We work across every major BI platform — Power BI, Tableau, Looker, Qlik, Apache Superset, and others. Our recommendation depends on your existing technology stack, your user base, and your governance requirements. Not on our preferences or partnerships.

For Microsoft-heavy environments, Power BI typically offers the tightest integration. For organizations that prioritize ad-hoc exploration and data storytelling, Tableau is often the right choice. For centralized, governed semantic layers, Looker excels.

But the platform is only part of the equation. The harder work — and the part that determines whether BI actually gets adopted — is understanding what your people need to decide, building the right metrics layer, and training your team to use it.

Frequently Asked Questions

What's the difference between analytics and business intelligence?

Business intelligence (BI) focuses on structured reporting and dashboards that describe what happened and why. Analytics is the broader discipline that includes BI plus predictive modeling, statistical analysis, and data science. In practice, most engagements include both — BI as the foundation, with analytics capabilities layered on as the organization matures.

Which BI platform should we use?

It depends on your stack and your users. Power BI integrates tightly with Microsoft 365 and Azure. Tableau excels at ad-hoc visualization and data storytelling. Looker is purpose-built for governed semantic layers. We evaluate your requirements and recommend the best fit — we're not locked into any vendor.

How long does a BI implementation take?

A focused dashboard project takes 4-8 weeks from requirements through deployment. A broader BI program — including data warehouse setup, semantic layer, multiple dashboards, and user training — typically takes 3-6 months. We deliver in phases so you see value early.

Do you train our team to use the dashboards?

Yes. Every engagement includes hands-on training for the people who will use the dashboards daily. We also build documentation and playbooks so new team members can get up to speed. The goal is self-sufficiency, not dependency.

Can you consolidate our existing BI tools?

Yes. Many organizations end up with multiple BI platforms across departments. We help inventory what exists, choose a single platform, migrate the highest-value dashboards, and decommission the old tools. It's one of the highest-ROI projects we see.

What if we already have dashboards but nobody uses them?

That's one of the most common problems we solve. Usually the issue isn't the tool — it's that the dashboards were built around available data instead of around the decisions people actually need to make. We rebuild from the decision point backward.

Learn more about analytics and BI

How to Consolidate BI Tools Without Losing Trust — a practical guide for organizations juggling multiple BI platforms.

What Is Business Intelligence? A Practical Overview — definitions, maturity stages, and what to expect from a BI investment.

Embedded Analytics for SaaS: What Product Teams Need to Know — building analytics into your product for customer-facing insights.

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Industries We Serve

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