With the release of Spotfire® 14.8 (also available for Spotfire 14.6.2 LTS and later), we continue to significantly expand the toolkit for industrial analytics. An additional 23 advanced, no-code algorithms, powered by the deep analytical engine of Spotfire Statistica®, have been added to our library of built-in data functions. This expansion builds upon the foundation of geoanalytics, time-series, and general analysis tools released last year, bringing decades of Statistica’s specialized expertise in machine learning, multivariate analysis, and high-fidelity data transformations directly into the Spotfire environment.
An improved integration
While it has long been possible to bridge Statistica® workflows into Spotfire, this latest update brings that analytical engine directly “under the hood” for a truly native experience. We’ve replaced the back-and-forth between environments with a frictionless interface that lives entirely within Spotfire. You can now deploy industrial-grade models instantly by selecting from a library of pre-configured algorithms, ideal for rapid, repeatable insights, or pivot to the Advanced mode to unlock greater control over statistical parameters for your most complex manufacturing challenges.
Accelerate advanced analyses in high-tech manufacturing
For manufacturers in the pharmaceutical and high-tech sectors, these 23 new algorithms transform raw sensor data into actionable intelligence by addressing the most critical stages of the production lifecycle. Quality control charts maintain the “validated state” by monitoring process stability in real-time. When deviations occur, multivariate analysis and clustering uncover “hidden signatures”, such as spatial defect patterns on a semiconductor wafer, that univariate tools often miss. To move beyond detection, correlation analysis and non-linear models are deployed to isolate the specific variables that truly drive yield loss, while normal distribution testing ensures that all processes meet quality readiness standards. Furthermore, signal smoothing and autocorrelation allow engineers to filter out equipment noise and analyze temporal behaviors to predict mechanical fatigue. Finally, the ability to score and reuse models means that once a Golden Batch or Ideal Yield is modelled, it can be operationalized to identify potential problems in production.
The road ahead: Automated insights with actions
Our team is actively expanding the library of Spotfire® Industry Pro Action Add-Ons to bridge the gap between advanced calculation and instant visualization. These specialized add-ons make it easy to deploy our new algorithms by automating relevant visuals. We are currently finalizing actions that simplify correlation analysis, provide diagnostics for model fitting, and enable one-click creation of quality control charts. Furthermore, new tools for auto- and cross-correlation will help users identify hidden temporal patterns across equipment and batches. Keep a close eye on the Add-ons screen within Spotfire as these powerful new capabilities go live to benefit manufacturing analytics.
To see how these capabilities can be applied in practice, join our upcoming webinar where we’ll explore how Statistica® is enabling more advanced, scalable industrial analytics within modern analytical workflows.
Discover how teams are applying statistical methods to uncover deeper insights, improve model reliability, and support more confident decision-making. Register now to secure your spot and learn how to bring advanced analytics into your everyday workflows.