Spotfire is the only data visualisation and predictive analytics dashboard, that contains an in-built commercial grade R engine, and is a recognised data prep leader by Forrester Wave.

From A$6,300/user + gst
(Contact us for US$ price)

Spotfire - Data visualisation and predictive analytics dashboard, that contains an in-built, commercial grade, R engine, and is a recognised data prep leader by Forrester Wave.

Spotfire Editions

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Spotfire interactive dashboard

Spotfire Desktop contains a user friendly interface for visualising data and creating interactive dashboards, without requiring a TIBCO Spotfire Server.

Spotfire AI driven recommendations.

AI-driven Recommendations

AI powered recommendations, instantly display visualisations for different relationships in your data. Making it faster and easier to get the insights you expect—as well as those that surprise.

Recommendations also help you mashup data from multiple sources in a single visualization—and load, link, categorize, and navigate data.

Spotfire predictive analytics
Built-in Predictive Analytics

Out-of-the-box predictive methods for regression, classification, clustering, and forecasting. Enable everyone with predictive analytics. Visualise input data and results in Spotfire interactive dashboards. Deeper data science calculations are available through TIBCO Data Science or Spotfire Data Functions, which leverage R, Python, SAS, and Matlab code.

Data science engine - TERR

Unique Data Science Language Integration

Build custom predictive models, through Data Functions. TIBCO® Enterprise Runtime for R (TERR) runs inside any analysis. Train R models (or python) and deploy with TERR. Use popular advanced analytics packages and databases. Integrate multiple tables, columns, and values with point-and-click visualizations, not possible with other products.

Spotfire location analytics and mapping

Unparalleled Location Analytics

Bring geographic context to your analysis with instant multi-layer maps, geocoding, and reverse geocoding. Maps help generate insights and make predictions not possible using tables and charts. Deeper geo-analytics can be done, using the built-in R engine and TIBCO® GeoAnalytics.

Real time streaming analytics

Real-time Streaming Analytics

Spotfire Data Streams continually pushes new data to Spotfire for real-time analysis. Create interactive dashboards with real-time IoT (MQTT, OSI PI), social, and messaging (TIBCO, JMS, Kafka) sources, as easily as with static data. Imagine what analytics can do for frequently changing data. To provide a real-time view into your business, continuous updates are pushed to users, enabling analysis and action while it still matters.

Past data can be added for full contextual awareness. Inventory management to financial fraud detection, and ground-staff operations to predictive maintenance, Spotfire® Data Streams augments your intelligence with the power of real-time analytics.

Feature List

User Interface

  • File import and export dialogs
  • Database import and export dialogs
  • Point and click dashboards are combination of visualisations and pages to showcase insights
  • Assists you in analysing the data by providing recommendations on visualizations that fit the data you want to display
  • Data Canvas provides an overview on how each data table in the analysis was created, and you can add data or edit settings for different data sources
  • When you add a visualisation to an analysis, you can:
    – Start by selecting data
    – Start by selecting visualisation type
    – Search for what you’d like to visualise
  • Copy-and-paste to Word, PowerPoint and Excel
  • Export visualisation to Image or PDF and data to a file
  • Export dashboard to PDF or Microsoft PowerPoint
  • Create custom toolbars
  • On-line help, manuals and how to videos

Integrate with many data formats

  • Load data into the internal data engine of TIBCO Spotfire (in-memory analysis) from a number of different sources
    – by pasting data from the clipboard
    – by dragging and dropping or opening simple text files, Microsoft Excel files or SAS files
    – by connecting to a database via ODBC or OLE DB
  • ASCII: fixed format, comma-separated, and tab-delimited – (*.csv), (*.txt)
  • Microsoft Excel Workbook
  • Spotfire Analysis file (*.dxp)
  • Script Function Definition (*.sfd)
  • TIBCO Spotfire Text Data format
  • Microsoft Access Databases
  • SAS (*.sas7bdat)
  • Universal Data Link (*.udf)
  • Sfs file (*.sfs)
  • Spotfire Server Log Files (*.log)
  • Spotfire Binary Data Format (*.sbdf)
  • ESRI Shape Files (.shp)
  • Amazon Redshift
  • Apache Drill
  • Apache Spark SQL
  • Attivio
  • Cloudera Hive
  • Cloudera Impala
  • Dremio
  • Google Analytics
  • Google BigQuery
  • Hortonworks
  • IBM DB2
  • IBM Netezza
  • Microsoft SQL Server
  • Microsoft SQL Server Analysis Services
  • OData
  • Oracle
  • Oracle Essbase
  • Oracle MySQL
  • Pivotal Greenplum
  • Pivotal HAWQ
  • PostgreSQL
  • Salesforce
  • SAP BW
  • Snowflake
  • Teradata
  • Teradata Aster
  • TIBCO Cloud™ Live Apps
  • TIBCO ComputeDB
  • TIBCO Data Virtualization
  • TIBCO Spotfire Data Streams
  • Vertica


  • Table
  • Cross Table
  • Graphical Table
  • Bar Chart
  • Waterfall Chart
  • Line Chart
  • Combination Chart
  • Pie Chart
  • Scatter Plot + add linear and non-linear statistical model curves with a few clicks
  • 3D Scatter Plot
  • Map Chart
  • Treemap
  • Heat Map
  • KPI Chart
  • Parallel Coordinate Plot
  • Summary Table
  • Box Plot
  • Text Area
  • Edit colours, lines, axes, annotations and layout
  • Interact with visualisations by marking, highlighting, drag-and-drop and zoom sliders
  • Multiple data tables in one visualisation
  • Hierarchies
  • Trellis Visualisations – create multiple charts conditioned by levels of one or more variables
  • Details Visualisations – selecting points on a main visualisation allows drill down on a 2nd and subsequent visualisations

TIBCO® Enterprise Runtime for R (TERR)

  • In-built high-performance statistical engine that is compatible with open-source R.
  • Provided in your installation of Spotfire so you can script and run data functions or create predictive models.
  • TERR Tools are provided to give you access to the TERR console to test scripts and functions, and to the TERR Language Reference for help with installed packages.
  • You can use TERR Tools to launch the RStudio interactive development environment for script authoring. TERR Tools also provides an interface to download and install packages from the Comprehensive R Archive Network (CRAN).
  • Note: Some statistical methods below are accessible through the TERR engine in Spotfire via data functions

Data Relationships

  • Linear Regression
  • Spearman R
  • Anova
  • Kruskal-Wallis
  • Chi-square

Cluster Analysis

  • K-means
  • Hierarchical clustering


  • Linear regression
  • Polynomial regression
  • Model diagnostics
  • Prediction and confidence intervals
  • Parametric spline models
  • Logistic regression
  • Generalized linear models
  • Visually compare polynomial regression and traditional methods

Hypothesis Tests and Confidence Intervals through TERR engine

  • One-sample and two-sample t-test and Wilcoxon
  • Paired t-test
  • Correlation: Pearson, Kendall’s tau, Spearman’s rho
  • Goodness-of-Fit: Chi-square, Kolmogorov-Smirnov, Shapiro-Wilk
  • Rank tests: Kruskal-Wallis, Friedman
  • Proportions: exact Binomial test, Normal approximation
  • Contingency tables and tests for independence: Chi-square, Fisher, Mantel-Haenszel, McNemar

Analysis of Variance

  • Univariate and multivariate ANOVA
  • Flexible specification of variables, covariables, interactions, nesting, transformations
  • F-test to compare two variances
  • Multiple comparisons: Fisher, Tukey, Bonferroni

Nonlinear Regression and Maximum Likelihood

  • Nonlinear regression
  • Nonlinear maximum likelihood
  • Constrained nonlinear regression

Nonparametric Regression

  • Loess smoother
  • Super smoother
  • Kernel smoother
  • Spline smoother

Tree Models

  • Classification trees
  • Regression trees
  • Pruning, shrinking, and splitting
  • Scoring

Multivariate Analysis

  • Canonical correlation
  • Factor analysis
  • Principal components
  • Biplots

Time Series Analysis 

  • Autocovariance, autocorrelation and partial autocorrelation
  • Box-Jenkins ARIMA models
  • Classical and robust AR
  • Seasonal decompositions
  • Fourier transformations
  • Classical and robust smoothers and filters
System Requirements
Processor2GHz or faster, Quad core  
(2 GHz, Dual core, minimum)
RAM8 GB or more
(4 GB, minimum)
Note: Large data sets can require more RAM.
Hard Disk 10 GB for installation and normal use.
Display1920×1080 pixel resolution or higher, 16-bit or 32-bit color depth
(1024×768 pixel resolution, 16-bit or 32-bit color depth, minimum)
Operating SystemMicrosoft® Windows 10
Microsoft® Windows 8, 8.1
Microsoft® Windows 7
Parallels Desktop 15 for MacOS X 10.10 – 10.15
Microsoft Office (Optional)To use Spotfire functionality that integrates with Microsoft Office products, such as exporting to PowerPoint, importing data from Access, and importing data from older versions of Excel, Microsoft Office must be installed. 
The following versions of Microsoft Office are supported: 
Microsoft Office 365 
Microsoft Office 2016, 32-bit and 64-bit versions 
Microsoft Office 2013, 32-bit and 64-bit versions 
Microsoft Office 2010, 32-bit and 64-bit versions