Oracle on Wednesday introduced the Fusion Data Intelligence Platform, an evolution of its Fusion Analytics Warehouse designed to better enable customers to take action from insights.
In addition, the tech giant unveiled new generative AI capabilities for Oracle Analytics Cloud aimed at making data consumers more efficient in their work.
The Fusion Data Intelligence Platform and Analytics Cloud updates were revealed during Oracle CloudWorld 2023, Oracle's user conference in Las Vegas.
Even before the latest tools were unveiled, Oracle's data management and analytics suite was comprehensive, according to David Menninger, an analyst at Ventana Research.
In particular, he noted that Oracle's natural language processing capabilities stand out.
David MenningerAnalyst, Ventana Research
"Oracle is among the leaders in part due to the breadth of its offering, its augmented analytics capabilities and its mobile offering," Menninger said. "Oracle was a leader with natural language processing even before ChatGPT and generative AI became popular, [and has] been offering robust multilingual NLP supporting dozens of languages for several years."
A few days before the conference, Oracle and Microsoft disclosed that Oracle's database services are now available on Azure, an acknowledgement that most enterprises deploy data on more than one cloud. Beyond making Oracle's database services available on Microsoft's cloud, the partnership makes Microsoft's OpenAI services available to Oracle customers.
Fusion Analytics Warehouse was Oracle's set of prebuilt applications for AI-powered self-service data management and analytics, including data preparation and data visualization.
The new Data Intelligence Platform, built with data lakehouse capabilities optimized for AI and machine learning, is the next iteration of Fusion Analytics Warehouse.
The Data Intelligence Platform comes with a spate of prebuilt features that deliver data as a service. Combined, their intent is to help users not simply analyze data and reach insights but also take action within their workflows based on those insights, according to Joey Fitts, vice president of analytics product strategy at Oracle.
"Throughout [evolution of analytics], what's been lacking has been the destination of helping someone get their job done, helping someone make a decision and actually take action," he said. "That's where we're focused. That's the guiding principle for [these updates]."
As a result, the Data Intelligence Platform not only aims to provide tools that enable users to take action but also delivers those AI, BI and data management tools in a single location. As a result, users don't have to change environments to go from discovery and insight to action.
"These shouldn't be disconnected," Fitts said. "We need to take the load off the everyday line-of-business professional so that they can take actions efficiently and effectively."
Prebuilt capabilities that come with the Data Intelligence Platform include the following:
- Automated data pipelines.
- Data models based on Fusion Cloud Applications data and other data sources to provide users with insights into their business.
- Prescriptive AI and machine learning models to automate certain time-consuming tasks and free workers to do more specialized tasks.
- Dashboards, reports and key performance indicators.
- Natural language query and automated insights to increase efficiency.
- And intelligent applications culling data from prebuilt models, AL/ML models and other analytics content.
In addition, the Data Intelligence Platform includes features for customers of Oracle's industry-specific analytics applications.
Fusion ERP Analytics now includes a new accounting hub and Fusion Supply Chain Management Analytics has new manufacturing analytics capabilities. Also, new payroll management tools are now part of Fusion HCM and Fusion Customer Experience now includes insights into how price and contract quotes affect customers.
Perhaps most significant is the overall intent to embed analytics within users' workflows, according to Menninger. While the individual capabilities are beneficial, what's truly important is enabling business users with data and analysis.
"As an industry, [analytics] still hasn't reached the majority of the workforce in most organizations," Menninger said. "Analytics embedded into business applications is a critical way to reach more of the workforce. Fusion Data Intelligence Platform and its manifestation in … applications is an effective way to get analytics into the hands of more line-of-business workers."
Beyond unveiling the Data Intelligence Platform, Oracle introduced new AI features for its Analytics Cloud, the vendor's business intelligence suite.
In the 10 months since OpenAI launched ChatGPT, which marked a substantial leap in generative AI and large language model technology, most data management and analytics vendors have made generative AI a focal point and unveiled plans for generative AI.
Embedded analytics specialist Sisense was among the first, revealing an integration with OpenAI in January. Just recently, Qlik unveiled a new portfolio for generative AI and machine learning; Domo built a set of tools to enable generative AI development; and Google introduced integrations between its data management and analytics tools and its generative AI capabilities.
Now, Oracle is doing the same.
Analytics Cloud now includes the following features:
- natural language interactions so users don't have to write code;
- automatically generated document summaries -- including in podcast form -- that explain key points and context; and
- recommended insights from dashboards and collaboration capabilities that enable users to share data assets in discussions through an integration with Microsoft Teams.
Combined, the new capabilities are designed to make data exploration and analysis easier and more efficient, according to Fitts.
"AI can be applied to lighten the load … across the entire analytics pipeline, from sourcing the data to structuring it, preparing it, cleaning it, visualizing it and then surfacing insights," he said. "All of [the new capabilities] are to lighten the load. Making life easier for people is what we hope AI is going to do for us."
Menninger, meanwhile, noted that just as embedded BI helps more people within organizations work with data, so does generative AI.
It's estimated that only about a quarter of employees within most organizations use analytics as part of their jobs. Generative AI, which enables natural language interactions, has the potential to greatly increase that use.
"Just as embedded analytics helps reach more of the workforce, natural language processing enhanced by generative AI is another way to expand the reach of analytics," Menninger said. "Generative AI also helps provide access to more AI and ML-based analyses. AI and ML still require specialized skills, and generative AI is helping to make it easier to create and access those types of analyses."
As Oracle plots its data management and analytics roadmap, one of the focal points will be to keep improving existing capabilities, according to Fitts.
For example, he noted that the Fusion Data Intelligence Platform is the rebranding of Fusion Analytics Warehouse, with new and improved features. Moving forward, Oracle plans to continue adding new features and improving existing ones within its data management and analytics suite.
"We describe this as a multi-year journey," Fitts said.
Regarding generative AI, he added that through a recent integration with Cohere, Oracle has plans to enable users to bring LLM capabilities to their own data and develop private language models that don't have the data security problems of public LLMs.
Menninger, meanwhile, said Oracle -- along with most of its competitors -- would be wise to invest more in planning capabilities that enable customers to ask, "What if?" of their data to explore different scenarios.
Oracle offers Essbase for such analysis, but it's separate from Analytics Cloud.
"I'd like to see further integration of Essbase driver-based planning capabilities with the Oracle Analytics Cloud, and more decision intelligence capabilities to help organizations evaluate the trade-offs between different courses of action," Menninger said.
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.