Tibco Evolves Data Analytics and Visualization with an Eye on AI
Enterprise analytics provider Tibco is today updating its software portfolio with a series of releases designed to help improve data analysis and visualization through improved scalability, streaming data and the integration of artificial intelligence (AI) capabilities.
This includes an update to Spotfire 12.2 with improved data visualization features as well as new data features for developers. Tibco acquired the original Spotfire technology in 2007 for $195 million. At the time, Spotfire positioned itself as a business intelligence provider, although the technology gradually evolved into an AI-powered data analysis and visualization platform.
Tibco ModelOps launched in July 2022 and is now more tightly integrated with Spotfire with the goal of enabling data scientists to build and deploy analytics workflows powered by AI models. Additionally, Tibco is updating its streaming data technology with a feature the company calls “dynamic learning” that enables data analytics operations on streaming data. The Tibco platform is also becoming cloud-native, with the ability for organizations to deploy software on Kubernetes infrastructure.
"We currently have deployments of up to 100,000 people accessing the web environment to interact with Spotfire analytics, and that can be resource intensive," Michael O'Connell, Director of Analytics of Tibco, told VentureBeat. "So being able to scale that horizontally with Kubernetes is really a big step up for us."
Along with data analytics, business analysts are usually the focus of Tibco.
That said, O'Connell pointed out that Tibco also wants to help developers building more sophisticated operations and data science initiatives. In the Spotfire 12.2 update, Tibco is introducing the concept of “mods” as a way to bring extensibility to the Spotfire platform. With the new extensibility, developers can code JavaScript in Spotfire to create visual analysis operations.
Going further, the new capabilities of data functions will make it easier for developers to take custom code and turn it into point-and-click analysis operations for business analysts.
The extensibility of data analysis and visualization can go even further than custom coding with Spotfire Cloud Actions features. Cloud Actions provides integration points with operational systems such as databases and enterprise applications to provide a bridge between data from the Tibco platform and external sources.
Dynamic learning arrives in the data streamData streaming is increasingly critical to business operations and data analysis.
One challenge is that streaming data often comes from an open-source Apache Kafka source and must be loaded into a database before it can be used for analysis or machine learning (ML).
With the new dynamic learning capability of Tibco's streaming data technology, O'Connell said organizations will now be able to train ML models directly from the event stream.
"In the case of dynamic learning, we have developed a set of methods to build and train any model directly on the event stream without the intermediate step of writing data to the database," he said.
One particular use case where dynamic learning is useful is in manufacturing. O'Connell said that with data coming from the manufacturing floor in real time, being able to understand and react to what is happening as it happens is critical.
The intersection of data science and ML is found in ModelOpsModelOps features first released on the Tibco platform in 2022 provide organizations with model management capabilities for data science and AI workflows.
Now, with Spotfire 12.2, ModelOps is more tightly integrated, enabling what O'Connell calls a complete data science lifecycle. Organizations can now train an ML model with the Tibco data science product which can then be cataloged and managed in Tibco ModelOps.
Finally, Tibco Spotfire users can find and use an ML model managed by ModelOps and use it for data visualization and analysis operations.
In the future, Tibco will integrate
Enterprise analytics provider Tibco is today updating its software portfolio with a series of releases designed to help improve data analysis and visualization through improved scalability, streaming data and the integration of artificial intelligence (AI) capabilities.
This includes an update to Spotfire 12.2 with improved data visualization features as well as new data features for developers. Tibco acquired the original Spotfire technology in 2007 for $195 million. At the time, Spotfire positioned itself as a business intelligence provider, although the technology gradually evolved into an AI-powered data analysis and visualization platform.
Tibco ModelOps launched in July 2022 and is now more tightly integrated with Spotfire with the goal of enabling data scientists to build and deploy analytics workflows powered by AI models. Additionally, Tibco is updating its streaming data technology with a feature the company calls “dynamic learning” that enables data analytics operations on streaming data. The Tibco platform is also becoming cloud-native, with the ability for organizations to deploy software on Kubernetes infrastructure.
"We currently have deployments of up to 100,000 people accessing the web environment to interact with Spotfire analytics, and that can be resource intensive," Michael O'Connell, Director of Analytics of Tibco, told VentureBeat. "So being able to scale that horizontally with Kubernetes is really a big step up for us."
Along with data analytics, business analysts are usually the focus of Tibco.
That said, O'Connell pointed out that Tibco also wants to help developers building more sophisticated operations and data science initiatives. In the Spotfire 12.2 update, Tibco is introducing the concept of “mods” as a way to bring extensibility to the Spotfire platform. With the new extensibility, developers can code JavaScript in Spotfire to create visual analysis operations.
Going further, the new capabilities of data functions will make it easier for developers to take custom code and turn it into point-and-click analysis operations for business analysts.
The extensibility of data analysis and visualization can go even further than custom coding with Spotfire Cloud Actions features. Cloud Actions provides integration points with operational systems such as databases and enterprise applications to provide a bridge between data from the Tibco platform and external sources.
Dynamic learning arrives in the data streamData streaming is increasingly critical to business operations and data analysis.
One challenge is that streaming data often comes from an open-source Apache Kafka source and must be loaded into a database before it can be used for analysis or machine learning (ML).
With the new dynamic learning capability of Tibco's streaming data technology, O'Connell said organizations will now be able to train ML models directly from the event stream.
"In the case of dynamic learning, we have developed a set of methods to build and train any model directly on the event stream without the intermediate step of writing data to the database," he said.
One particular use case where dynamic learning is useful is in manufacturing. O'Connell said that with data coming from the manufacturing floor in real time, being able to understand and react to what is happening as it happens is critical.
The intersection of data science and ML is found in ModelOpsModelOps features first released on the Tibco platform in 2022 provide organizations with model management capabilities for data science and AI workflows.
Now, with Spotfire 12.2, ModelOps is more tightly integrated, enabling what O'Connell calls a complete data science lifecycle. Organizations can now train an ML model with the Tibco data science product which can then be cataloged and managed in Tibco ModelOps.
Finally, Tibco Spotfire users can find and use an ML model managed by ModelOps and use it for data visualization and analysis operations.
In the future, Tibco will integrate
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