How Spotfire Uses Data Science & Geospatial Analytics

As industries continue to experience fast-paced technological change, data sits at the heart of transformation. Few understand this imperative as acutely as Michael O’Connell, Chief Analytics Officer at Spotfire. With a background rooted in data science, AI and industrial analytics, Michael brings decades of experience spanning pharmaceuticals, manufacturing and the energy sector.

Spotfire, now an independent entity after its spin-out from enterprise software firm TIBCO, is doubling down on its mission to enable organisations – particularly those in energy, manufacturing and life sciences – to extract operational and strategic insight from complex data. Its platform is designed not just for analysts, but for engineers, scientists and business decision-makers who need both comprehensive analytics and accessible visualisation.

“Spotfire’s core mission is to help people interactively explore data to find insights and put those into operations to move the needle on their business,” says Michael, adding that the platform seeks to serve as “the UI for AI on people’s data.”

As the global energy sector embraces digitalisation and the pressure to optimise operations grows, tools like Spotfire are fast becoming indispensable.

All about Spotfire

Originally born from research and development in chemistry and biology, Spotfire quickly gained traction in energy and manufacturing. Over the years, the product has expanded – particularly during its time within TIBCO – integrating capabilities from geo-analytics to data streaming and advanced data management.

“We’ve come back to the roots of Spotfire,” Michael explains. “We were invented in R&D and soon after that, we got into energy and manufacturing. The product evolved a lot during our time inside TIBCO. We’ve acquired geo-analytics software, data management and streaming data science software, baking all of that into the Spotfire platform.”

Today, Spotfire boasts sector-specific strengths, addressing challenges faced by scientists, engineers and quantitative experts across energy, manufacturing, pharmaceuticals, transport, logistics and finance.

According to Michael, Spotfire’s development has always followed the needs of its users. Its customer base is broad but focused: “It’s really the areas where there are engineers, scientists, quants – people who want combined visual analytics with data science. That’s Spotfire.”

Competitors include the likes of American big data analytics company Palantir, as well as industry specialists such as Seek, Corver and Minitab in manufacturing. But Spotfire distinguishes itself by embedding deeper data science rather than focusing solely on business intelligence dashboards. 

“We are much more data science than BI,” Michael says.

Breaking down data silos

A critical issue across energy and sustainability is data fragmentation – data lives in different systems, formats and scales. Spotfire’s approach is to provide flexible data access, regardless of infrastructure.

The company’s hybrid in-memory architecture means it can connect with and ingest enormous datasets. 

“Our fifth-generation hybrid in-memory data engine allows you to do that on very, very big data,” Michael says. This enables users to prepare and transform their data interactively.

Spotfire connects directly to cloud data warehouse leaders such as Snowflake and Databricks, as well as legacy systems like Google BigQuery, Microsoft SQL Server and Amazon Redshift. The platform also supports industry-specific formats – including well log data vital for oil and gas workflows.

“We also have our own data services layer – Spotfire® Data Virtualization – which allows users to combine multiple source systems into unified, virtualised views,” Michael explains. Data can be cached, transformed or scheduled as needed, giving customers fine-grained control over data flow and performance.

A unique feature is Spotfire’s data canvas, which tracks every action – filter, transformation, calculation – in an intuitive, visual interface. Unlike traditional, laborious box-and-arrow data pipelines, Spotfire makes data preparation accessible and auditable.

As Michael puts it: “Whether you bring your data in through an interface or have a conversation with it using AI, you still need robust data connections. That’s where we’ve made a lot of investments.”

Visualisation and geospatial analytics: Seeing beyond the obvious

The visual dimension of analytics is increasingly essential for sustainability and energy transition. Spotfire’s platform includes a wide range of built-in visualisations, from standard graphics to advanced 3D subsurface models relevant in upstream oil and gas.

The platform’s JavaScript extension ecosystem lets users and partners develop new visualisations, encouraging a collaborative community. Michael notes: “We have an active community – over 9,000 downloads of community-generated visualisations and more than 50 specialised for industry applications.”

Spotfire’s “multilayer map” feature stands out in the geospatial analytics world. This capability, enhanced by technology from past mapping software acquisitions and integration with geographic information system (GIS) leader Esri, allows users to build complex, layered spatial analyses. In energy, for example, an engineer can overlay geological data, production metrics and well locations, enabling insights into how sub-surface features drive performance.

Michael describes the sophistication: “You might have geology on one layer, well locations on another, then calculate how production relates to property features.”

But these multilayer maps have applications far beyond geography. In semiconductor manufacturing, for example, map charts represent wafer patterns – vital in optimising chip yields at the nanometre scale.

“As you build up and manufacture a wafer, you have multiple layers, each with masking or etching patterns for circuits. You’ve got to get those very accurate. Major manufacturers trust Spotfire for multi-layer maps, measuring overlay down to three nanometres,” Michael explains.

Data science algorithms

Energy and manufacturing companies don’t just need to see their data, but to model and predict behaviour. Spotfire delivers advanced spatial and temporal algorithms built into its platform.

“Our strength is the ability to run data science algorithms directly on the map,” Michael notes. This includes smoothing spatial data to identify yield patterns, edge effects on semiconductor wafers, or production hotspots across oil fields.

Spatial models help users understand underlying relationships – where, for instance, a drop in oil pressure may indicate blockages before equipment fails. The platform allows the overlay of polygons to aggregate data, enabling ‘type curves’ for resource forecasting and production benchmarking.

Spotfire’s “point-in-polygon” methods help integrate disparate datasets – combining geological surveys with production results and well logs for decision-making clarity.

Michael emphasises the flexibility: “We do nearest neighbour analysis, proximity modelling, buffer zones and coordinate integration. It’s about spatial interoperability – combining different measurement types for advanced calculations.”

Accelerators for real-world use cases

One of Spotfire’s priorities is moving users from theory to action. The platform offers industry “accelerators” – pre-built analytics examples designed for energy, manufacturing and beyond.

“In energy, for example, we have accelerators for real-time drilling, completions, production surveillance and energy trading,” Michael says. Users plug in their data and quickly see actionable visuals, from drilling rate projections to production forecasts.

Manufacturing accelerators support everything from predictive maintenance to digital twins, helping companies optimise their shop floors and anticipate breakdowns before they happen.

Advanced time series analysis has also become central to Spotfire’s offering. The ability to summarise, smooth, or compare patterns across time or depth – using recent innovations like dynamic time warping – enables operators to make sense of high-frequency equipment readings and geological data.

Michael explains: “Say you drill two wells of different depths, with similar geology but at different scales. Our methods can ‘warp’ those patterns to align them, helping you transfer learnings from one site to another and improve outcomes.”

Scalable, governable and fine-grained deployment

Large enterprises need to balance flexibility with control. Spotfire addresses this with licensing and governance designed for granular permissioning.

Features such as Spotfire’s data virtualisation track precisely who can see which data – down to the row, column or even individual value. Licence management allows organisations to apportion features between different user types, ensuring compliance and budgetary control.

“It’s helpful for administration in complex setups,” Michael says, particularly where intellectual property and regulatory constraints demand strict data segregation.

AI-powered exploration

Generative AI is the trending disruptor – but integrating it meaningfully into scientific, engineering and sustainability workflows is the real challenge.

Spotfire’s solution is to embed “copilots” – intelligent AI assistants that help users with everything from data navigation to configuring sophisticated analyses. Michael believes generative AI is changing the nature of business intelligence toolkits: “It feels like BI dashboards are becoming replaceable by chatbots… We position away from basic visualisations into industry analytics. AI is transforming basic tools into conversational interfaces.”

But for the deep industrial and scientific analysis on which sectors like energy depend, the human-AI connection is vital. Copilots can rapidly assemble complex multi-layer maps or run time series comparisons, but users retain control – ensuring trust and rigour in decision-making.

A key innovation, Spotfire Actions, allows users to string together configurations – such as building a multilayer map – in a series of repeatable, shareable steps. Communities can exchange these artefacts, supporting rapid innovation and best practice sharing across sectors.

Optimising production in oil and gas

For upstream energy clients, Spotfire’s value becomes clear on the production floor. Engineers deploy the platform to monitor “non-productive time” – analysing pressures, temperatures and current draws on artificial lift systems to anticipate failures before they disrupt output.

“Production surveillance and optimisation is a key use case. You want to reduce non-productive time, monitor downtime reasons and quickly resolve issues,” Michael explains

The platform’s predictive tools allow real-time monitoring and forecasting not just of physical performance, but also of financial outcomes – informing everything from early maintenance to SEC filings. Benchmarking features support comparison against industry data, enabling users to measure performance, investigate anomalies and improve efficiency.

Wider benefits include the reduction of unnecessary costs, the prevention of ‘frack hits’ where one well affects another and the integration of geological, seismic and petrophysical analysis to optimise both production and environmental safety.

More visualisations, more data science, more use cases

The drive for carbon efficiency, cost savings and operational excellence means that data-driven innovation will remain central to the energy sector’s future. For Spotfire, the roadmap is clear: deeper verticalisation, more analytics accelerators for core use cases, expanding AI-powered workflows and ongoing partnerships with industry leaders.

“In the next 12 to 18 months, we’re focused on more of the same: going deeper into verticals, more visualisations, more data science, more use cases,” Michael says.

Gen AI and agent-based AI will “continue to mature,” while data cataloguing and metadata will “enable even more AI applications,” he continues.

Amid the high-velocity evolution of the industry, Michael never loses sight of the humans at the helm. “Our world is so fast-paced. You have to deliberately slow down, stay curious, humble, grateful and kind.”

In a sector where every decision has immense consequences, Spotfire’s fusion of human insight with machine intelligence looks set to keep it at the heart of sustainable progress for years to come.