Over the last few years, the analytics tools available to geoscientists and engineers have become more powerful and, in many cases, more complex and expensive. For smaller technical teams, that’s forced a rethink — which tools actually help us do better work, and which ones simply add overhead? Lately, I’ve found myself reflecting not just on the tools I use, but on how the data analytics landscape itself has evolved.
When I joined Canadian Discovery back in 2018, Spotfire quickly became my go-to tool for making sense of complex subsurface data. At the time, it felt like the perfect bridge between geoscience and analytics — powerful, flexible, with strong geospatial capabilities. We used Spotfire to dig into relationships between pressure, temperature, fluid chemistry, and well production — relationships that are discussed in this SPE paper I co-authored on the Montney Formation. It also became a critical tool during our work on the Northeast BC Geological Carbon Capture and Storage Atlas, where we needed to evaluate pressure distribution at depth and examine porosity–permeability trends to help identify which areas and zones were most suitable for long-term CO₂ storage. Over the last few years, we’ve also used Blue River Analytics’ Analytics for Energy Suite, built in Spotfire, to run decline curves and forecasts for CDL’s Play Maps and Catalyst.
Over the last six months, however, I’ve found myself spending more time in a different ecosystem — studying for the Microsoft Power BI Data Analyst certification and the PL-300 exam. While Power BI wasn’t originally known for its geospatial capabilities, those features have steadily improved, particularly for business-focused mapping. With options like Azure Maps and ArcGIS integration — along with external visuals such as ZoomCharts and Icon Map — Power BI can now support a wide range of geospatial use cases.
But why the shift? For me, a big part of it comes down to the direction Spotfire itself has taken. Over time, it’s moved away from competing directly with tools like Power BI and Tableau, and toward a space dominated by enterprise-level platforms and highly specialized, industry-specific visualizations. And while I’m genuinely wowed by the dashboards showcased at their recent Energy Forum, that shift comes with a price point that’s becoming increasingly out of reach for individuals and smaller companies.
Seeing this play out across multiple teams made the implications hard to ignore. As Spotfire continues to move up-market, many smaller companies are being forced to make pragmatic decisions about where it still makes sense… and where it doesn’t. Power BI often emerges as a natural complement or alternative, not because it replaces Spotfire’s depth, but because of its accessibility and tight integration with tools many teams already rely on, like Excel. Used together — or thoughtfully split across different workflows — the two platforms can cover a lot of ground.
This changing landscape is what led my husband and I to expand our conversations beyond tools and toward something bigger. Matt specializes in database architecture, database management, and application development, and together we saw a growing gap in the oil and gas data analytics space — especially for smaller companies. There’s a real need for practical, affordable analytics support that helps teams better understand and integrate their data, without pushing them toward expensive software or enterprise-scale solutions. After a conversation with management at CDL, we decided to forge a new path and start ClearCurrent Analytics. Our focus is straightforward: helping companies use the tools they already have — or are already paying for — to explore their data in more effective and cost-conscious ways.
This post is the first in a series we’ll share throughout 2026. While we can’t publish client work, we’ll be working with publicly available datasets — including those from the British Columbia Energy Regulator Data Centre and the Alberta Energy Regulator Products and Service Catalogue — and bringing them together to showcase data structures, workflows, and visualization use cases. The goal is to share practical ideas that help teams get more value from the tools they already use. If this is something you’re navigating as well, I hope you’ll check back regularly and follow along as the series unfolds.