TIBCO Spotfire Cheat Sheet

Updated 2026-05-23

Next Topic: What-If Analysis and Scenario Planning Cheat Sheet

TIBCO Spotfire is an enterprise business intelligence and visual analytics platform that combines in-memory analysis, in-database connectivity, and a rich expression language to let data analysts and scientists explore data interactively. It matters because it bridges self-service exploration for business users with advanced scripting and statistical integration for data scientists — all inside a single, governed, server-managed environment. The key mental model to hold: almost everything in Spotfire is relational — markings propagate across tables, filtering schemes are document-level objects, and the OVER function family changes the scope of any aggregation without leaving the expression editor.

What This Cheat Sheet Covers

This topic spans 15 focused tables and 130 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Data Loading and SourcesTable 2: Information Designer and Information LinksTable 3: Data Canvas and TransformationsTable 4: Marking and Filtering SchemesTable 5: Calculated Columns and Binned ColumnsTable 6: Custom Expressions and the OVER FunctionTable 7: Ranking FunctionsTable 8: Scatter Plots and TrellisingTable 9: Data Functions — TERR and R/Python IntegrationTable 10: IronPython ScriptingTable 11: Spotfire Mods and SDK ExtensionsTable 12: Spotfire Server and Library AdministrationTable 13: In-Database AnalysisTable 14: Spotfire X and AI/Recommendations FeaturesTable 15: Property Controls and Dashboard Interactivity

Table 1: Data Loading and Sources

The starting point of any Spotfire analysis is getting data in. Spotfire supports a spectrum of loading strategies from pasting clipboard data to live in-database queries, and choosing the right one determines performance, refresh behavior, and what downstream features are available.

Type	Example	Description
In-memory import	Drag-and-drop a `.xlsx` or `.csv` onto the canvas	• Data is loaded into Spotfire's internal engine • all calculations and filters run in-process. Fastest interactivity, but limited by client RAM
Data Connection (connector)	Files and data → Connect to → SQL Server / Snowflake / Oracle	• Native connector to a database • data can be imported (in-memory) or kept external (in-database). Preferred over ODBC when a native connector exists
Information Link	File → Open From → Library → select an information link	• A pre-built, reusable database query stored in the Spotfire Library • built in Information Designer from column, filter, and join elements • Abstracts SQL from end users
In-database (external data)	Files and data → Connect to → [Connector] → keep as External data	• No data is stored in Spotfire at runtime • every visualization triggers a live query • Supports Teradata, Oracle, SQL Server, SAP HANA, etc

Table 1: Data Loading and Sources

Type	Example	Description
In-memory import	Drag-and-drop a `.xlsx` or `.csv` onto the canvas	• Data is loaded into Spotfire's internal engine • all calculations and filters run in-process. Fastest interactivity, but limited by client RAM
Data Connection (connector)	Files and data → Connect to → SQL Server / Snowflake / Oracle	• Native connector to a database • data can be imported (in-memory) or kept external (in-database). Preferred over ODBC when a native connector exists
Information Link	File → Open From → Library → select an information link	• A pre-built, reusable database query stored in the Spotfire Library • built in Information Designer from column, filter, and join elements • Abstracts SQL from end users
In-database (external data)	Files and data → Connect to → [Connector] → keep as External data	• No data is stored in Spotfire at runtime • every visualization triggers a live query • Supports Teradata, Oracle, SQL Server, SAP HANA, etc