1. Home
  2. Complex Event Processing Software
  3. TIBCO BusinessEvents Reviews
  4. User Review of TIBCO BusinessEvents
TIBCO Spofire review.
May 09, 2018

TIBCO Spofire review.

Paolo Avalle | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with TIBCO BusinessEvents

It is used across the whole organization addressing problems spanning from R&D to financial analysis.
  • Dashboard for real-time analysis
  • R-scripting, although the R editor could be improved, there are syntax inconsistencies between R-studio and R-opensource in TSSS
  • Basic statistics and drill down capabilities
  • Better integration with R versions and better debug for R-scripts in Spotfire. There are inconsistencies in syntactic expressions accepted by R-studio and not accepted in Spotfire. Accelerating the debug would be awesome. Having a command like View (data frame) that directly output in the dashboard would be a great accelerator.
  • Self-taught
  • Positive: dashboard is very informative and extremely powerful
  • Negative: we need to have more capability for data integration - OR for prototyping data integration and analytics, without resorting to something complex and big like StreamBase (which is truly amazing) but requires too much specific knowledge for industrial application. something easier to learn would be great. for example, I was able to learn KNIME and prototype a solution in a week. But StreamBase is too complex.

Standard dashboard for basic statistics. GREAT

Advanced multivariate modeling needs to be coded in R for example, LESS GREAT. You would get a million users for off-the-shelf multivariate modeling like SIMCA.

The integration with Statistica is a great idea but much of its success will depend on the speed and the ergonomics by which you integrate the development workflow for multivariate models PLS/PLS-DA/ PCA etc.

You should implement some of the features offered by SIMCA (Sartorius Stedim) and expand the multivariate analysis offering and more advanced tools (from Random Forest to T-SNE and machine learning / AI). You will get lots of 'love' from pharmaceutical engineers. :)