Over the past year, the team here at Spotfire has been doubling down on our mission to lead in visual data science, a discipline that brings together interactive visualizations, advanced analytics, domain expertise, statistical thinking, and scalable analytics to solve high-value, real-world problems.
We’ve sharpened our product strategy, restructured our offerings, and invested deeply in capabilities that serve the engineers, scientists, analysts, and decision-makers who rely on Spotfire every day. This renewed focus has shaped how we innovate, how we serve customers, and yes, even how we engage with industry analyst reports.
As a part of these efforts, we chose not to participate in the 2025 Gartner Magic Quadrant (MQ) evaluations for Analytics & BI (ABI) and Data Science & ML (DSML). This decision reflects a deliberate repositioning, not just of our business, but of our vision for visual data science, the visual-first approach to data science.
Why we’re focused on visual data science
Spotfire is built for those solving complex, domain-specific problems, from nanometer-scale process optimization to real-time logistics monitoring.
We’re guided by a different vision—one that centers on:
- Visual-first exploration and insight generation
- Domain-informed analytics and decision-making
- Reusable, interactive applications that drive operational value
Our users aren’t just data scientists or business executives; they include engineers, scientists, quants, and process owners. People who know their field inside out, and need tools that help them think with data, act fast, and iterate visually.
Why we didn’t participate in the MQs
While Gartner’s MQs for ABI and DSML offer helpful frameworks for many buyers, the categories are increasingly focused on technologies and use cases that diverge from our customers’ reality.
On ABI: Spotfire users go far beyond static dashboards and reporting on historical KPIs. They build rich, interactive, often industry-specific data applications that combine analytics, geospatial insights, statistical modeling, and automation. These aren’t reports, but rather operational systems used by thousands of people across Fortune 500 enterprises to guide day-to-day decisions.
On DSML: Spotfire empowers engineers, scientists, business analysts, quants, and domain experts (users who know their domain deeply and understand how to apply visual analytics and statistical thinking to real-world challenges). These users often apply and tune machine learning models, but they’re not focused on academic model-building, MLOps pipelines, or building foundational models from scratch. That’s not their goal. Their goal is insight, informed decision-making, and actionable business outcomes.
In short, Spotfire doesn’t fit the traditional mold of ABI or DSML as defined by these Magic Quadrants, and we’re okay with that.
What we’re building instead
Spotfire is not just holding steady; we’re pushing boundaries. The Spotfire visual data science platform continues to empower businesses in tackling complex challenges with enhanced efficiency and accuracy. Earlier in the year, we launched our refined suite of products, solutions that cater to diverse business requirements while optimizing value and user-friendliness with a visual-first approach to data science. Our roadmap and recent innovations reflect our belief in the future of visual data science:
Spotfire® Analytics: Ideal for intuitive data exploration, this package enables analysts to spot trends swiftly and unearth insights through visual data wrangling, geoanalytics, and AI-driven recommendations.
Spotfire® Data Science: Designed for domain experts and data scientists, this package integrates predictive modeling, machine learning, and process optimization. It addresses industry-specific hurdles, from boosting operational efficiency in manufacturing to improving patient results in healthcare.
Spotfire® Enterprise: Crafted for large-scale organizations, this solution unifies analytics, automates workflows, and guarantees strong governance. Its enterprise-level features facilitate seamless team collaboration and effortless compliance.
Our customers use Spotfire to tackle complex, high-value problems in some of the world’s most data-intensive industries:
- Discovering gene-compound relationships in life sciences R&D
- Optimizing manufacturing yields at the nanometer scale
- Accelerating clinical trials and lab automation
- Designing subsurface programs for energy exploration
- Monitoring transport and logistics performance in real-time
- Automating compliance and operational analytics in finance
And they do all of this by harnessing the power of Spotfire, with built-in visual data science tools, reusable UX components, interactive and generative AI, robust governance, industry-specific analytics, and scalable deployments—all in one integrated environment.
The future is visual
We believe the most pressing business problems won’t be solved by dashboards or pipelines alone, but more so by people with deep expertise and the right tools to explore, understand, and act on data. That’s what Spotfire delivers.
We’re proud of where we’re headed, and while we’re not in this year’s MQs, we’re more aligned than ever with the needs of the industries we serve. 2025 continues to be a landmark year for Spotfire and visual data science. To find out more or discuss our decision not to participate in the Gartner MQs this year, do not hesitate to contact one of our experts.
Spotfire® 14.5, our latest release, delivers next-level analytics, automation, and enterprise management. Visit our What’s New page and join our What’s New webinar series to learn about the latest and greatest from Spotfire. Experience the power of visual data science for yourself with our new Spotfire Data Science trial, and explore your data like never before.