Oracle Analytics Cloud at Oracle CloudWorld 2022

October 24, 2022 | 5 minute read
Barry Mostert
Senior Director, Artificial Intelligence and Analytics
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October 2022 is going to be an exciting month! Not only is Oracle hosting the first ever Oracle CloudWorld event in fabulous Las Vegas, but there are three significant Oracle Analytics Cloud updates coming to the platform. These updates provide greater depth to existing functionality to better support:

  1. Data modelers with a new enterprise semantic modeler,
  2. Citizen data scientists through better integration with AI/ML services,
  3. and business users with new automated insights.

1. Semantic modeling and multi-user development

For over two decades, Oracle Analytics has had a rich enterprise semantic model that helps deliver consistent and trusted numbers. Until now, creating, editing, and publishing the semantic model (aka RPD) has been limited to a desktop tool. However, the next generation of semantic modeler is entirely web-based and introduces new functionality never originally available through the desktop tool. The new functionality provides a seamless, multi-user developer experience with tight Git integration. And it includes a new Semantic Model Markup Language (SMML) for more flexible methods to edit and update models. For example, users can now make updates directly through code rather than through the tool’s user interface.

New semantic modeler with Git integration
The new semantic modeler with Git integration


“This is the real game-changer for the entire Oracle Analytics community”

Vyshak Palanisamy & Slaven Mandic, ClearPeaks

Web access with Git integration allows all internal analytics users the ability to contribute their business knowledge to the centralized semantic model, effectively democratizing the enterprise semantic layer. As the varied nature of data sources grows, this distributed approach allows the business to contribute to the organization’s data-mesh and not rely or wait on IT for such updates. Using Git, semantic layer content can be versioned, merged, branched, and managed by other types of Git operations. Final submissions can go through checks and approval processes before being integrated into the primary model.

This capability has been highly anticipated and will have real positive impact for analytics practitioners. ClearPeaks, one of Oracle’s systems integrator partners had this to say, “… the new integration with Git offers a real multi-user experience where dozens of different users can work on the semantic model simultaneously, without the risk of their changes being overwritten by someone else when published. This is the real game-changer for the entire Oracle Analytics community, making the development of new models faster, more efficient, and more fun!”

Read more about the new Semantic Modeler

Watch a demo of the Semantic Modeler

2. AI/ML new integrations and enhancements

Oracle Analytics is embedded with machine learning capabilities (ML) for all levels of users, from advanced users that know the commonly used algorithms and how to tune them, to users who want a simple code-free experience to apply ML to their data sets. The new capability allows you to extend the ML functionality already built-into OAC with other OCI services such as the OCI Vision service. OCI Vision is an AI service that applies computer-vision technology to analyze image-based content. Now, OAC can render the information into a familiar, easy-to-read dashboard. In addition, seamless integration with OCI Functions allows OAC administrators to register the OCI functions directly into OAC, and then business users can execute those functions in their data flows without the need to code. Further integration with other OCI AI services are currently in development.

OCI Vision (AI service) with Oracle Analytics Cloud for image recognition and classification
OCI Vision (AI service) with Oracle Analytics Cloud for image recognition and classification

In this image detection and classification example, Oracle’s Ben Arnulf (Senior Director, Analytics Product Strategy) has used his doorbell camera to capture images, leveraged OCI Vision to identify himself, classified a variety of attributes about what the camera is seeing, and then displayed the findings in an OAC project.

Watch a demo using OAC with OCI Vision

3. Advanced composite visualization and proactive automated insights

This update has two parts, Advanced Composite Visualizations and Auto-insights. These capabilities aim to increase productivity, especially for business users, by simplifying analytics projects and using unbiased machine learning to generate analytics-driven insights.

Advanced Composite Visualizations

As the world gets more complicated every day, so does the data we require to understand it. This means larger amounts and wider varieties of data that needs to be processed and considered in our business decisions. With business users gaining access to an organization’s data-mesh, much more data is brought into analytics projects – great for decisions, hard for dashboard design. Ultimately, this additional complexity can, unintentionally, end up in our analytics visualization projects while trying to show all the relevant information simultaneously. A denser way to deliver more information faster is needed, but at the same time without increasing the dashboard’s complexity. A new capability in Oracle Analytics Cloud helps to organize content and reduce the complexity of building and maintaining dashboard projects. It’s called Advanced Composite Visualizations. These new composite visualizations allow the author to easily add additional metrics onto a variety of graphics while reducing the effort to manage and maintain the dashboard. Overall, this capability reduces the number of individual visualizations, but increases the information density on the dashboard without making it look busy or cluttered.

Six advanced composite visualizations displaying multiple metrics
Six advanced composite visualizations displaying multiple metrics


Using machine learning to find analytics-driven insights is something all companies are striving to achieve, but how do you make that ML capability available to those users who really need it? Auto-insights is an easy-to-use, 1-click capability that allows OAC to analyze your data set and make smart recommendations for visualizations based the unbiased findings it discovered. OAC proactively analyzes data sets and uses ML to produce automated insights about its findings. The visualization recommendations are quickly added to an analytics project with a single click, boosting productivity while building a compelling story for stakeholders. 

Gain machine learning generated auto-insights about your datasets
Gain machine learning generated auto-insights about your datasets


Watch this demo of OAC’s Auto-insights capability

Oracle Analytics Cloud is frequently updated with new capabilities for all types of users, from data specialists to ordinary business users. OAC is built to help you easily connect your organization’s data sources and create or expand a data-mesh, making it easy to retrieve any relevant information and display it clearly so that you can build your analytics-driven stories that lead to better business decisions. 

To stay on top of what’s new, follow us on YouTube and LinkedIn where we’ll make announcements and provide video demos.  For the latest news, product updates, events and success stories follow us on Twitter @OracleAnalytics, and connect with us on LinkedIn.  Or try Oracle Analytics for yourself in a hands-on workshop.

Barry Mostert

Senior Director, Artificial Intelligence and Analytics

Barry is a senior director for product marketing covering Oracle's AI and Analytics services.

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