The SAP HANA connector now supports SAP HANA 2. The connector supports both relational and multidimensional data.
When using Spotfire connector for Azure SQL and SQL Server, now you can specify the database manually, removing the need to have access to the master database to connect to the database.
You can now change the row height in table visualizations and details-on-demand by dragging with the mouse. It makes it easier to create better looking, more readable tables.
A new REST API lets external applications upload SBDF-formatted data to the Spotfire library. You can then easily access the data in multiple Spotfire analysis files using any Spotfire client connected to the same Spotfire library.
For analyses using the titled tab navigation mode, Spotfire Consumer users can now navigate to any page using a drop down. This makes it faster and easier to go the desired page.
The Spotfire in-memory data engine now supports lag and leap functions.
You can now use the .Net API to configure the number of lines of text in a graphical table column header.
In addition to today's tab separated files, the .Net API for exporting data files now supports .csv formats with values separated by commas or semicolons.
Just use the contextual header popover, opened by clicking the table header.
When adding a new marking in the data section of the visualization properties dialog, the list of markings is now auto-scrolled so the new marking will be in view. This makes it easier to manage multiple markings when there are many in the analysis.
A new row "filter rows" data transformation enables you to remove rows based on what you have selected in filters. If you know the values you have selected in a filter are the only ones of interest, you can remove all other corresponding values (rows) with one click. This automatically creates the new transformation, automatically documented in the data canvas, and editable as any other data transformation type.
You can also insert a filter rows transformation manually from the summary view when adding imported data, or later from the canvas.
Further, you can remove rows based on dates by accessing the expression editor through the data canvas.
You can now export data to .csv files with values separated by commas or semicolons in addition to today's spaces and tabs. This makes it easier to import data that has been wrangled in Spotfire into other programs that sometimes only support these delimiters. Just use Export > Data to file like before.
It's now possible to reload not only all linked data sources as before, but also stored data sources, from the Data menu of Spotfire Analyst. When using stored data sources this is useful because they usually just need to be refreshed periodically.
You can also reload linked and stored data sources via the Spotfire API, when, for example, you want to add custom reload buttons in a text area to be used by Spotfire Consumer web client users.
It's now possible to trigger a reload of multiple data tables at once from the Data Table Properties dialog.
You can now review the values selected in prompts by looking at the information for the data source node in the data canvas. Previously, you had to reload your data to review the selected prompt values.
When a transformation is added or modified, the scroll position is now kept so the added or modified transformation is still visible. When a transformation is deleted, the scroll position is retained so you get a confirmation of the operation.
When adding a calculate and replace column transformation, the default column name is now automatically set to the selected column name.
Spotfire native connectors now support the following new database versions:
Please use the corresponding connector to connect to the above data sources.
You can now reload individual data sources, both linked and stored, via the Spotfire C# API. This is useful, for example, when you want to add custom reload buttons in a text area to be used by Spotfire Consumer web client users.
The Spotfire C# API now allows for empty values to be propagated to custom row method implementations. Empty values may, in many cases, have special meaning, and with this API addition, those cases can now be handled in a custom row method.
It is now possible, via the Spotfire C# API, to configure the AutoCreateFilters property on a data table. By setting the property to false (default is true) users can manage filters manually and decide whether or not they want to create filters for certain columns.
The Spotfire C# API has been extended with operations to rename, copy, move, and set metadata (description, keywords, and properties) on library items. These operations can be called from custom extensions or from IronPython scripts.
Now you can use the Spotfire C# API to browse for Spotfire Automation Services jobs stored in the Spotfire library directly from the LibraryManager class or using the LibraryBrowserDialog UI.
The Automation Services API now provides the following runtime parameters for custom tasks:
The new version of the Java User Directory API is easier to use with more capabilities, giving it the same options as the User Directory web service:
The Spotfire C# API now exposes FilterRowsTransformation, used to filter out rows that don't match the given expression. The more generic ExpressionTransformation now includes a where clause property. This API is useful when you want to add transformations to a data table using IronPython scripts or custom extensions.
You can build visualizations from the new search bar. Type, for example, "Sales per region and year" and the Spotfire systems respond with recommendations for visualizations.
Search and mark values in your data from the new search bar. For example, if you are looking for the sales of a specific sales rep or sales in a specific country, just type in the name and the Spotfire system will mark it.
The search bar also lets you search and run virtually any Spotfire functionality. For example, add a calculated column or similar, even for data stored in the library.
Visualization recommendations powered by AI and machine learning help you find relationships in the data. If you select a column in Data in Analysis, the Spotfire system now shows recommended visualizations, including other columns that seem likely to have a relationship to the selected column.
A completely reimagined user experience with a beautiful interface makes it easy to find and work with all functions and tools.
A completely reimagined user experience with a beautiful interface makes it easy to find and work with all functions and tools. "Files and Data" lets the user browse and search for all kinds of data sources, files, data functions, data connections, custom data sources, etc., both locally and in the library.
"Data in Analysis" lets the user see details about the selected column, such as the distribution of values, max, min, unique values, etc., and access various functions for columns.
"Visualizations" lets the user choose a visualization type and drag-and-drop it on the visualization area.
"Data Canvas" is where users can review and author the data pipeline for each data table in the Source View. Access it using the icon at the bottom of the Authoring bar on the left.
By connecting to the new Spotfire Data Streams software, or TIBCO Live Datamart, Spotfire Analyst can now visualize data from dozens of streaming sources such as Kafka, MQTT, Salesforce Streaming, WITS, OsiPi, many capital market exchanges, and of course, other TIBCO technologies such as TIBCO Messaging.
For streaming data, you can limit the time range shown in the visualization to the last N minutes or any other time range you want to see.
When creating a visualization from the visualizations flyout, chose one from "Search or Recommended Visualizations" and drag it where you want it on the canvas.
Set a preferred aggregation method for individual columns, but also a globally preferred aggregation for numerical columns.
The prepared PDF reports can now be configured to display the current user and/or the current time in the header or footer.
Spotfire Business Author users can now configure the coordinate reference system (CRS) and projection of a map chart and its associated layers.
Over 160,000 new cities are now available worldwide. New administrative areas are supported for the US that include area code, borough, CBSA, congressional district, and school district.
When adding and replacing data, the Summary View will not only show you how your data will be added, it will also recommend how data should be added.
Since the Summary View is displayed before data is loaded, you are now able to define Add Columns and Add Rows operations without loading one of the data tables into memory first.
The recommendation engine is built right into the Summary View and will run across all listed tables. This allows the recommendation engine to work across tables not yet loaded into the analysis file.
Just like with Add Rows recommendations, you can configure Add columns in one step, before loading data.
The visualization recommendation engine is now an integrated part of the data panel. There is also a new type of recommendation available, recommended table links.
As with in-memory data tables, in-database data tables are now easier to navigate because their columns are automatically categorized and grouped by numbers, categories, currency, time, location, identifiers, and binary.
A native connector for Apache Drill is now included, available in the "Connect to" list in the Windows Spotfire Analyst client. The connector works in conjunction with the MapR Drill ODBC driver.
A native connector for Dremio is now included, available in the "Connect to" list in the Windows Spotfire Analyst client. The connector works in conjunction with the Dremio ODBC driver.
A new way to list connectors makes it easier to find the data source you want to connect to. Each connector also has updated help text that helps you instantly find details on working with the connector.
All data-related menu items are now moved to a Data menu.
In the new Automation Services area of the administration interface, you can schedule Automation Services jobs and monitor the activity of all Automation Services jobs that are run in your Spotfire environment.
The TERR service is now available as part of the Spotfire environment, along with the existing Web Player service and Automation Services.
Scheduled update jobs that cannot be immediately run are now all queued on the Spotfire Server for distribution to Spotfire Web Player instances as they become available. This results in a more robust routing of jobs than before when each service maintained its own job queue after its maximum number of concurrent updates was reached.
At the DEBUG logging level, the node manager now produces a performance.monitoring.log file that is similar to the server log file with the same name.
The create-scheduled-jobs command creates scheduled Automation Services jobs from a local JSON file that is created by the administrator. That remove-config-property command modifies the configuration.xml file to remove the value(s) of a specific configuration property.
An API can get or set the preferred aggregation method to be used by plot heuristics when creating aggregated expressions from a data column.
An API can load the default layer, for example, base map layer, TMS layer, or feature layer, when configuring a map chart.
Now rows, columns, and data transformations can be added anywhere within an existing data table structure.
Spotfire now has a new and improved Salesforce connector that supports federated authentication and doesn’t need an ODBC driver. It uses Salesforce bulk API for quick access to millions of Salesforce records and allows loading of more than 2000 rows from Salesforce reports.
Spotfire now supports cascading filters also when working with external data in relational databases.
Spotfire now automatically sets coordinate reference systems by recognizing the projection formats (.prj file) associated with Shapefiles.
More coordinate reference systems are now supported with greater details.
Spotfire now has a query log dedicated to connectors available for administrators. The log file collects queries from Spotfire Analyst, Node Managers and Automation Services.
You can now create visualizations that aggregate calculated Oracle Essbase measures.
The connectors for Oracle, Microsoft SQL Server, and PostgreSQL now support geographical data types allowing you to connect to and extract geographical row-level data into the in-memory data engine with just a few configuration steps.
In addition to the new connection timeout setting for SAP HANA, any connection strung parameter can now be set from Spotfire, for example, the fetch size.
The maximum MDX query timeout limit can now be raised to allow for queries that take longer time.
Username and password authentication is now supported for Microsoft Analysis Services.
With the added support for username and password authentication you can now connect Spotfire directly to Microsoft Azure Analysis Services.
TIBCO Cloud Spotfire and the Spotfire on-premises platform can now connect to Amazon RDS SQL Server data using Microsoft SQL Sever connector. This means Spotfire analysis files stored in the Spotfire (Cloud) library can query Amazon RDS SQL Server directly from the web-based clients, Spotfire Business Author and Consumer.
With the new authentication mechanism, JavaScript API can be used on a Spotfire Server that is configured with any external/web authentication. For example, you can now create a mashup with a .dxp file located on the TIBCO Cloud Spotfire library.
It is now possible to add data operations (AddRowsOperation, AddColumnsOperation or DataTransformationOperation) to any location within the data table structure (Source View).
Big data visualizations using live queries, especially towards large OLAP data sources like SAP BW and Oracle Essbase, are now much quicker to respond to and also mark changes you make.
Visualizations with zoom-sliders that now auto-zoom when the data changes (e.g, when filtering) and when sliders are at the end of their range.
Spotfire Analyst now has a color picker that makes it easy to create analyses that follow your corporate color scheme, the color scheme of a website or the like. Just pick the color you want from anywhere on your screen and use it in the custom theme editor.
The Spotfire page layout is now responsive, so when a page is viewed on a small device like a phone, the layout organizes to suit the screen. The responsive layout enables vertical scrolling if the page is too large to view on the screen directly.
The column selectors in Spotfire now have an improved look and feel and are only displayed in the visualization over which the mouse pointer is positioned.
You can now add columns to a data table using Spotfire Business Author web client.
You can edit previously specified Add columns (Join) operations. This makes it really easy to adapt your analysis files to changes in your data sources over time.
You can now quickly edit on-demand settings for each individual data source in a data table.
You can store analysis files in the TIBCO Cloud Spotfire library and query Databricks Cloud and Apache Spark SQL directly from the web-based clients Spotfire Business Author and Consumer.
TIBCO Cloud Spotfire now connects to Microsoft HDInsight Hive. You can store analysis files in the Spotfire Cloud Library and let them query Microsoft HDInsight directly from the web-based clients Spotfire Business Author and Consumer.
TIBCO Cloud Spotfire and the Spotfire on-premise platform now support Amazon EMR via Hive and Apache Spark SQL.
A timeout setting has now been added to the Cloudera Impala connector. This allows you to let Impala queries run for longer. For example, this allows running queries to complete when you are extracting result data sets into the in-memory data engine of Spotfire.
Execution of Automation Services jobs can now be triggered from an external application using a REST API. A job can either be stored in the Spotfire library or passed as an argument. The API uses an OAuth2 based authentication/authorization mechanism.
The Web Service (SOAP) APIs (LibraryService, UserDirectoryService, UpdateAnalysisService, InformationModelService, LicenseService and SecurityService) now uses a OAuth2 based authentication/authorization mechanism. This means that the API client only needs to support a single authentication method that will work with any Spotfire Server authentication configuration.
Spotfire now has an updated and simplified procedure for building .NET extensions for Spotfire. The package building functionality is now integrated with Visual Studio® along with templates.
It is now possible to ship a bundled solution, containing several Spotfire packages, as a single distribution file (.sdn).
The Spotfire deployment mechanism now supports both upgrading and downgrading of the installed Spotfire client when you connect to a server (and a specific deployment area), making it easier to work with multiple Spotfire versions simultaneously.
You can now temporarily maximize a visualization to take a closer look without distorting the original layout as well as rotate the view between all visualizations on the page.
Two-finger scroll is now possible on mobile devices, very useful when viewing a page larger than the screen and when looking at a visualization with its own scroll capability, like a table or a map. Two fingers scroll the page, one scrolls the visualization.
We have increased the limit for number of labels in a scatter plot or a map chart to up to 3,000, especially useful for centered data labels where markers don't overlap significantly.
In the source view, you can remove individual data sources using the new trash can button. Spotfire provides a preview of the result as you mouse-over the trash can. The undo feature, of course, allows you to reinstate the node.
Joining data tables with Insert Columns now stores which columns you chose to ignore and which to add, listing them in the data table properties dialog of the source view. This is very useful when many data transformation and Insert Columns operations are in your analysis.
With Spotfire's connector for Teradata, you can now browse and connect to data represented by Teradata macros. A macro allows you to name a set of one or more SQL statements, providing a shortcut for executing groups of frequently run SQL statements in Teradata.
Now you can export a prepared PDF with the Spotfire .Net API, including custom workflows with C# extensions or IronPython scripts.
The Spotfire .Net API page renderings and visualizations now result in PNG images that use the visual theme, and the API includes settings to adjust resolution and visibility of attributes like annotations, axis labels, legend, and title. This API is useful when creating export tools to support customized layouts or output formats.
The Spotfire .Net API now supports configuring a WMS layer with username and password.
The Data Table Source View API (introduced with the 7.10 release) now lets you remove individual data sources or other operations, such as add columns operations or add rows operations.
