Capabilities
Data Analytics
Transform raw data into actionable insights that drive informed decision-making and competitive advantage.
Data Platform Design
Architect modern data infrastructure that scales with your business and enables advanced analytics.
Business Intelligence
Build dashboards and reporting systems that provide actionable insights to decision-makers.
Real-time Analytics
Process and analyze streaming data to enable instant insights and automated responses.
Data Governance
Establish policies and practices that ensure data quality, security, and compliance.
Data Analytics Consulting for Decisions, Not Dashboards
Plenty of businesses are drowning in dashboards and starving for decisions. Reports multiply, every team has its own version of the numbers, and the metrics that actually drive the business are buried under vanity charts nobody acts on. Effective data analytics consulting starts by reversing that order: decide which decisions matter, then build only the data products that inform them. Interactive Intel is an operator-led, founder-delivered boutique based in Miami, and we bring an operator's impatience to analytics work. We are not interested in a prettier dashboard. We are interested in the three numbers that, if your team watched them weekly and acted on them, would change how the quarter ends.
Our 10/20/70 methodology applies directly here. Roughly 10 percent of analytics value comes from the algorithms and statistical techniques, 20 percent from the data platform and pipelines, and 70 percent from the people and process work that determines whether anyone actually changes a behavior because of what the data says. A flawless dashboard that no one trusts or uses is worth nothing. So we spend our time making the numbers trustworthy, putting them in front of the right people in the cadence they actually work in, and closing the loop so insight turns into action.
A Single, Trusted Source of Truth
Most engagements begin with a familiar problem: the same question gets a different answer depending on who you ask, because each team pulls from its own spreadsheet. We fix that by designing a modern, right-sized data platform, typically built on Supabase and Python pipelines, that consolidates your operational data into one governed source. We are deliberate about scale. A growth-stage SME does not need a sprawling enterprise warehouse; it needs clean, reliable, well-modeled data that a small team can actually maintain. Data governance is part of this from the start: clear definitions, access controls, and quality checks so that when a number changes, you know why.
On top of that foundation we build business intelligence that fits how decisions really get made. As illustrative examples, a hospitality operator might get a weekly view tying occupancy, channel mix, and staffing cost to margin; a clinic might track schedule utilization, no-show rates, and claim turnaround in one place, with patient data handled under the same FHIR and HL7 governance we apply across healthcare work. The goal is never more charts. It is fewer, sharper views that a manager opens on Monday and acts on by Tuesday.
Real-Time Where It Earns Its Cost
Real-time analytics is powerful and frequently oversold. Streaming infrastructure is worth its complexity only when a decision genuinely has to happen in seconds, such as flagging an anomaly, triggering a restock, or routing a customer in the moment. For most of what a growth-stage business needs, a reliable daily or hourly refresh is both cheaper and entirely sufficient. Part of honest data analytics consulting is telling you when you do not need the expensive thing. We build real-time pipelines where they pay for themselves and resist them where they would just add fragility, and that judgment is exactly what an operator-led partner is for.
From Analytics to Action
The hardest and most valuable part of any data analytics engagement is the last mile: turning a clear insight into a changed behavior. A dashboard that shows rising customer acquisition cost is only useful if someone owns the response and the organization has a rhythm for acting on it. This is the 70 percent of the work, and it is where our operator background matters most. We help establish the weekly or monthly review where the numbers are actually discussed, define who is accountable for each metric, and make sure the data product is wired into the moment a decision is made rather than sitting in a tool people open once and forget. Where it makes sense, we connect analytics to downstream automation, so that an insight does not just inform a person but can trigger an agentic workflow that acts on it, closing the loop between knowing and doing.
How We Engage
Clients usually start with an AI Readiness Audit ($5K–$15K) that assesses the state of your data and identifies the highest-value analytics or automation to build first. The flagship Agentic Workflow Sprint ($25K–$60K) then delivers a working data product or platform, instrumented so you can see the return. Larger organizations coordinating analytics across multiple regions move into Enterprise engagements from $150K. As the agentic-AI practice of Alton Group Worldwide, we keep the team small so founders deliver the work, and we measure success by decisions changed, not dashboards shipped. If you want data analytics consulting that ends in better decisions rather than another report nobody reads, that is precisely what we build.