Advanced Analytics in TIBCO Spotfire®
Advanced Analytics is a term often used for Predictive and Prescriptive Analytics. Spotfire has built-in capabilities for statistical analysis and modeling available directly from the user interface. These include calculated columns, expressions in visualizations, visualization features such as boxplot comparison circles and line chart forecasting and Tools menu data relationships, clustering and modeling. These built-in capabilities can be quickly extended to incorporate custom calculations of any complexity using TIBCO® Enterprise Runtime for R and other advanced analytics engines.
Watch a short demo of Spotfire advanced analytics:
Out-of-the-Box Advanced Analytics
You can create predictive models and apply advanced techniques from the Spotfire user interface.
- Calculations: Aggregations on Visualizations, Expressions - multiple Quick Reference topics
- Statistical Features: Clustering, Box plots & comparison circles, Relationships between categorical variables (Chi-square) - multiple Quick Reference topics
- Data Relationships Tool - The Data Relationships tool is used for investigating the relationships between many column pairs. The Linear regression and the Spearman R options allow you to compare numerical columns, the Anova option will help you determine how well category columns categorize values in (numerical) value columns, the Kruskal-Wallis option is used to compare sortable columns to categorical columns, and the Chi-square option helps you to compare categorical columns.
- Predictive Analytics: Regression Models, Holt-Winters Forecast - multiple Quick Reference topics
- Clustering: Data clustering is the process of grouping things together based on similarities between the things in the group. See how Spotfire makes it easy to perform clustering
Machine Learning & Advanced Analytics with TERR, Statistica and other Engines
You can use R models and run them within Spotfire using the in-built TIBCO® Enterprise Runtime for R engine, as well as leveraging advanced analytics from Statistica, SAS, MATLAB, KNIME, S+, Spark, H2O, MapReduce, Fuzzy Logix and databases.
- Predictive Analytics in Spotfire using TERR and other Advanced Analytics Engines - main Wiki page
- TIBCO® Enterprise Runtime for R (TERR) - main Wiki page
- Python Data functions in Spotfire - Spotfire 10.7 and later includes a Python engine that makes it easy to use Python for machien learning and other advanced analytics in Spotfire.
- TIBCO Statistica provides a comprehensive suite of data wrangling, statistics, machine learning and big data capabilities available via user-friendly, drag-and-drop visual workflows.
- Machine Learning Wiki page: Machine Learning algorithms learn from the data to produce detailed models that can identify complex patterns and make highly accurate predictions. They are well suited to use cases such as micro-segmentation, personalization, root cause analysis of complex processes, fraud detection and customer churn.
- Big Data Wiki page: Advanced and Predictive Analytics via integration with Spark, H2O, MapReduce and Fuzzy Logix big data engines
- Anomaly Detection page
- Try Spotfire Predictive Analytics Demos
- TERR Data Functions in Quick Reference Topics
- Spotfire advanced analytics components on the Exchange: Download data functions and analysis templates that enable you to easily extend Spotfire advanced and predictive capabilities.
- TIBCO Analytics Meetup (TAM) Webinars. This page offers a series of videos with tips and tricks about using Advanced Analytics in Spotfire. By the Data Science team.
- Predictive Analytics Webinars, Customer Stories and Use Cases
Back to Main Spotfire Wiki page