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Following the recent release of native Python data functions, users of TIBCO Spotfire® Analyst software now have a tool for managing locally used Python packages via a UI-based tool. This provides an alternative to managing these via the command line, with greater ease for importing Python packages into data functions.
It's now possible to configure Spotfire visualizations so that data can be limited by the same markings that visualizations employ. This allows for greater interactivity with drill-downs from any angle in any visualization, accelerating discovery by enabling faster time-to-insight.
The TIBCO Spotfire connector for Oracle MySQL now includes support for all of the following:
The SAP BW connector now supports SAP BW/4HANA 2.0.
The SAP HANA connector now supports auto binning.
The add rows recommendation has been made smarter and now uses data that has been loaded in the background.
The data loading progress dialog provides more information than before and enables users to copy the details into Spotfire software for further analysis.
Locate new details quickly; view details about selected library items, such as information links, right in the library browser for greater efficiency.
This also allows for copying to the clipboard from other programs or systems including new fields: "Modified by," "Date created," "Created by," "Modified by," "Path," "Library URL," "Web client URL," as well as "Columns" and "Prompts" details for information links.
In both Spotfire web and installed clients, it's now possible to automatically reconnect to the Spotfire Data Streams server if it's ever unavailable or restarts. Applications will now automatically reconnect without the need to reload data, which is especially useful for dashboards on public displays.
Spotfire Analyst installation procedures have been modernized and made more user-friendly. During package downloads, progress indicators are more accurate and visual designs of installation screens have been updated.
In addition, it's now possible to Whitelabel the SetupLauncher progress screen, which is useful for OEM applications.
Spotfire admins are now enabled to create custom configurations in the toolbar and set these preferences at the individual user or group level.
Labels for feature layers in map charts are now positioned automatically on geometries center without the need for any X/Y coordinate data. This makes it easier to visualize spatial features from files without coordinate information. Additionally, Map chart is now capable of rendering shapefiles and geoTIFF images even if the projection definition is not officially supported by Spotfire software, by reading and applying the projection definition contained in the imported file.
Web authors can now add and edit image layers like they are used to in the Analyst client. Image layers may also now be used to layer images over a geographical map, or, use images as a map background for geographical or non-geographical analysis.
The C# API now allows for:
The server upgrade process has been simplified with the Spotfire Server upgrade tool, which now:
As part of an upgrade process or scaling operation, any server in a Spotfire Server cluster can now be taken offline, and all users currently connecting through that server may seamlessly continue sessions on another server without re-authenticating (via load-balancer rerouting).
All running analysis sessions in the web player can also continue without losing their current state.
On top of existing OpenID Connect support to verify the identity of end users based on the authentication performed by an authorization server, the addition of support for initiating OpenID Connect login from a third party.
The OpenID Connect specification describes an optional feature through which a third party (such as an identity provider or a portal of some sort) may initiate login on a service provider.
Examples of third-party identity providers are Google, Azure AD, Okta, etc. See ThirdPartyInitiatedLogin within the OpenID Connect Core specification for more information.
Users of TIBCO Spotfire® Analyst software can now use Python libraries for math, statistics, artificial intelligence, and machine learning to build data functions for applications directly within Spotfire® analytics. Now supported natively, this tight integration between visual and advanced analytics allows users to drive computations of Python data functions interactively, with the same ease that users of R language packages always have. For more information, visit TIBCO Community.
The regular Spotfire server package deployment mechanism can now be used to deploy Python packages to users as needed.
A new "show/hide" property on Spotfire analysis pages permits authors to specify whether certain pages are made visible in "Viewing" mode. This feature allows greater flexibility for customizing analyses for various consumer audiences and also gives authors the ability to disable the page navigation options altogether or turn off navigation entirely to further tailor the experience.
Additionally, the Spotfire API now allows developers to programmatically inspect and change the visibility of a page in "Viewing" mode with custom extensions or scripts.
It's now possible for geoanalytics users to leverage a "great_circle_distance" function for calculating geo-spatial distance between two points. This feature enables easier estimation of arrival times and visual alerts. Additionally, new streaming data functionality was also introduced for modulus and concatenate string operators.
For more functions available in streaming data, see the TIBCO Streaming documentation.
Map charts now support zooming in/out as well as panning when Auto-Zoom is enabled.
Newly introduced capabilities for Business Authors now include the configuration of image layer transparency in Map charts, as well as the coloring of lines and borders for feature layers on Map charts.
The connector for SAP BW in Spotfire has been updated for the latest security libraries of SAP, including support for constrained Kerberos delegation in Spotfire web clients as well as Spotfire Analyst clients.
The connector for PostgreSQL in Spotfire now supports accessing data from Azure Database for PostgreSQL. This allows for users to optionally combine push- down queries with extraction of row- level data up front or on-demand.
The Salesforce connector in Spotfire has been updated to support more columns in a single view, making it possible to execute multiple requests and join results in Spotfire’s in-memory engine.
Users of TIBCO Spotfire® web clients can now visualize real-time streaming data sources in the same visual analytics environment as historical analyses.
This feature makes it easier to roll-out real-time business applications and dashboards to large user bases. A new demo file is now embedded in Spotfire® Analyst software to demonstrate streaming data using static data as reference.
When Spotfire users mark data points of interest, the Spotfire Recommendations engine now analyzes potential relationships between marked data and the broader datasets. Identifying the differences for deeper investigation, Spotfire analytics highlights these through best-practice visualizations for each specific relationship.
In Spotfire Analyst software, you can now configure alerts using the Spotfire Data Streams/TIBCO Streaming UI for visualizations based on real-time streaming data. With a simple right-click from within Spotfire analyses, users may now define and manage alerts, triggering actions such as sending of emails.
Spotfire software now uses georeferenced information to position image layers automatically rather than manually.
Additionally, adding image layers to a map chart allows for faster configuration of coordinate system (CRS) on full map visualizations.
With 50+ new analytical functions to the built-in Snowflake connector, Spotfire users leveraging the leading cloud data warehouse are now enabled to push more calculations into Snowflake. This reduces the need to extract row-level data from Snowflake into the Spotfire data engine.
Single sign-on (SSO) between Spotfire and Spotfire Data Streams software is now supported. This feature makes it easier to deploy streaming visual analytics dashboards and applications across large organizations.
The user now has the ability to inform the Spotfire solution not to calculate insights for selected columns of data. This aides in faster arrival at insight if data is redundant or otherwise irrelevant to a specific analysis.
Spotfire software now supports deployment on Windows Server 2019 as well as Oracle 19c as the Spotfire Server Database.
Creating TIBCO Spotfire® visualizations is now faster with enhanced Recommendations logic: automatic detection of several new non-additive categories, as well as more options for aggregating numeric columns. The Recommendations engine now uses that knowledge to make more informed suggestions for the initial state of visualizations, speeding the time-to-insight discovery.
Native Spotfire connectors for Cloudera Hive and Cloudera Impala now support the latest Cloudera CDH version. Available in all clients for on-premises and in TIBCO Cloud™ Spotfire® Analyst software.
A simplified workflow for data transformations: Add new data directly from the canvas graphical view using the canvas wire "plus sign" feature. Additionally, the canvas information pane now enables the user to copy to clipboard. Total row and column count details are also now available for each data source.
It's now possible to configure the Spotfire® Node Manager to run under non-administrative accounts. This feature distinguishes node manager operations from administrator operations on your machines. See this community article for access to the script and instructions.
With native Google BigQuery support, data scientists can now easily push interactive queries from Spotfire® software into BigQuery and visualize their largest datasets instantly without sacrificing speed or performance.
Native connectivity for self-service access to TIBCO ComputeDB™ in-memory database, which is based on Apache Spark™ and Geode™ software and optimized for analytics. Provides Spotfire users with modern query processing techniques for low-latency, interactive analytics on both stored and real-time streaming data.
TIBCO Cloud™ Spotfire® web clients now include support from TIBCO® Data Virtualization software, allowing web and mobile clients to load and refresh data. This offers unified views of disparate data sources and improved data federation capabilities.
With new, global-preference, on-demand storage, administrators have the option to let users begin a Spotfire session with empty on-demand data tables. Users will enjoy the ability to save and reuse analysis files with personal on-demand data tables or simply save storage space in the library.
Creating visualizations is now faster with the option of keyboard shortcuts: CTRL+1 creates a table, CTRL+2 creates a cross table. More shortcuts can be seen by simply hovering over the visualization type. Additionally, more time-saving features for quickly adding visualizations include the ability to search for chart types using the Find tool and simple keywords like "bar" or "line."
It's now possible to reload data directly from the toolbar in Spotfire web clients:
A new "Open" choice in the Spotfire file menu lets you browse local files.
The C# API allows IronPython scripts or C# extensions that allow admins to access user name, domain, group/role membership, and other relevant information about users.
Spotfire Server software now automatically includes ODBC drivers for Apache Spark SQL, Apache Cassandra®, and MongoDB Server. As part of this release, these have all been updated to the latest versions for TIBCO Drivers 1.8.
The Spotfire user action log has now been extended to include many common visual analytics actions such as create visualization, filter, export, and others. This enables organizations to monitor usage more closely and further optimize investment in BI assets.
This release adds support for a native connection to Snowflake, a widely deployed cloud-hosted data warehouse. Modern and scalable, Snowflake's elastic cloud provides TIBCO Spotfire® users with computing power on-demand, from ad-hoc visual data discovery to AI and machine learning workloads.
Advanced applications using scripts and custom queries now benefit from state of the art SHA-512 based trust stamps. Through a new security feature, data functions are now covered by the trust mechanism. Administrators will enjoy improved governance over authoring and execution using the new find-analysis-script command.
Additional notes for Admins on 10.3 upgrade requirements
Spotfire® analytics, along with TIBCO Cloud™ Spotfire® software, now support a native connector for TIBCO Cloud™ Live Apps low-code integration. This requires a TIBCO Cloud™ account and access to a TIBCO® Live Apps subscription.
Additional data connectors also include new native support for MongoDB, MemSQL, and MariaDB. Allows for live querying, retrieval, and in-database analysis from these top frameworks, all within Spotfire software.
The AI-powered recommendation engine now visualizes auto-detected relationships between selected columns and latitude or longitude more clearly, displaying them in maps. Additionally, over 4,000 new geo-coding boundaries are also now available in maps.
It's now possible to edit or remove top-level columns directly from the data canvas, along with other calculations or custom hierarchies, for a much cleaner data wrangling experience.
The ability to create custom headers in the Spotfire web client has been reintroduced, offering greater customization for co-branding and OEM white labeling capability.
Spotfire Server software now supports OAuth2 authorization code grant for the library REST API and other REST and SOAP-based services. Additional improvements to C# API include streamlined data table reloading and maps functionality.
As a result of user feedback following the Spotfire X software release, several feature enhancements to library browsing make it much easier to sort and locate full description fields through new hover interactions. The enhancements provide overall speed and performance gains.
Spotfire administrators are now able to set and manage licenses from the administration web UI. Licenses determine the features that members of a particular group can access.
Upgrading Spotfire Server is easier than ever with remodeled scripts structure, configuration files, and custom extensions. More of your settings are retained during server upgrades, and the upgrade tool can now be used for upgrading between service packs and deleting services as well.
These improvements have led to important changes in server directories. For more details, see Community.
Spotfire Server now supports custom display names as alternative URLs to the server, making it easier for users to locate the servers to connect to. Within Users and Groups, it's also now possible to search for Group members.
Additionally, it's now possible to configure the web player to capture either small or large dumps when it is nonresponsive.
There is also a new action log category for licenses: exclude_license. It indicates that the license feature was removed from the group's enabled license.
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 lead 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.
It is now possible to add data operations (AddRowsOperation, AddColumnsOperation or DataTransformationOperation) to any location within the data table structure (Source View).