The July 2026 update for Oracle Analytics Cloud (OAC) expands the ways teams can create reusable analytics content, control filter and chart interactions, deploy semantic models, and work with AI. New capabilities include shared calculations, filter groups, and data actions; finer-grained filter controls; additional data bar and overlay chart options; deployment of semantic models to resource groups; model selection for Oracle Analytics AI Assistant; and the Preview Oracle Analytics Cloud Model Context Protocol (MCP) Server. Together, these enhancements can help teams reduce repeated configuration, apply consistent logic across workbooks, and tailor analytics experiences to specific business needs.
Featured highlights:
AI and Generative AI
- Selecting Your Model for Oracle Analytics AI Assistant
- Oracle Analytics Cloud MCP Server (Preview)
Data Visualization and Experience
- Shared Calculations
- Shared Filter Groups
- Shared Data Actions
- Set Parameter Data Actions with Multiple Parameters
- Fine-Tuned Filter Interactions
- 100% Data Bars in Tables and Pivots
- Additional Stacked Layers in Overlay Charts
Modeling, Preparation, and Connectivity
- Deploy Semantic Models to Resource Groups
AI and Gen AI
Selecting Your Model for Oracle Analytics AI Assistant
Organizations can now choose which supported AI model powers supported AI experiences in Oracle Analytics Cloud. Administrators use the Generative AI settings in the Console to select an available model or register a supported managed gpt-oss model in Oracle Cloud Infrastructure Generative AI (OCI Generative AI). This flexibility can help organizations align model selection with their AI strategy and deployment requirements without changing how users interact with Oracle Analytics Cloud.
Oracle Analytics Cloud MCP Server (Preview)
The Preview Oracle Analytics Cloud Model Context Protocol (MCP) Server provides compatible AI clients with a standard way to interact with analytics content using natural-language requests. Once connected, an AI assistant can discover data sources, retrieve metadata, query results, locate or update workbooks, manage catalog content, and export outputs such as PDFs, subject to the permissions assigned to the authenticated Oracle Analytics Cloud user. By bringing common analytics tasks into an AI-guided workflow, this Preview capability can help streamline tasks and reduce manual steps, making it easier for teams to find, adapt, and share analytics content.
Data Visualization and Experience
Shared Calculations
Shared calculations allow workbook authors to create a business formula once and add it to the Shared Objects folder for a dataset or subject area. Authors can then use the calculation in other workbooks connected to the same data source. When an authorized user updates the shared calculation, the change applies to the workbooks that use it. This can help teams avoid recreating the same formulas and support consistent business logic across analytics content.
Shared Filter Groups
Authors can combine multiple filter conditions into a filter group and add the group to the Shared Objects folder for the underlying dataset or subject area. Other authors can then use the shared filter group in workbooks connected to the same data source. Authorized users can update the group centrally when business requirements change. Reusing centrally managed filter logic can help simplify dashboard authoring, support consistent audience definitions, and reduce variation in how teams filter the same data.
Shared Data Actions
Authors can make a data action shareable across workbooks that use the same dataset or subject area. For example, an action might open a related page or direct users to another resource. Other workbook authors with the appropriate access can use the shared action without recreating it. This can help provide more consistent navigation and interactions across analytics content while reducing repeated configuration and maintenance.
Set Parameter Data Actions with Multiple Parameters
Workbook authors can use a single Set Parameter data action to update multiple parameters. Authors map each parameter to a relevant data field, and when a user selects a data point in a chart or table, the associated values are passed to the corresponding parameters. This interaction can update connected elements such as filters, labels, text, and visualizations. It can help keep related workbook content synchronized and reduce the number of separate actions authors need to configure and maintain.
Fine-Tuned Filter Interactions
Enhanced filter settings give workbook authors more precise control over how filters and visualizations interact across a canvas. Authors can apply available filters, exclude filters, or select the specific filters and visualizations that should interact. The More option also allows authors to choose which filters narrow the values shown in a dashboard filter. These controls can help teams create more focused dashboard experiences and reduce the likelihood that unrelated filter selections affect an analysis.
100% Data Bars in Tables and Pivots
Data bars provide an at-a-glance visual comparison within measure columns in tables and pivot tables while keeping the underlying values visible. Authors can use the 100% Bar option and configure properties such as bar width, direction, value placement, color, transparency, and range. This compact presentation can help business users identify leaders, gaps, and patterns without leaving the detailed table.
Additional Stacked Layers in Overlay Charts
Overlay charts support additional layer types, including 100% Bar, Stacked Area, and 100% Area charts. Authors can combine these layers with other chart types that share the same categories while selecting a different measure, visualization type, and formatting for each layer. This flexibility can help teams compare related information, review how results are distributed across groups, and examine trends in a coordinated view.
Modeling, Preparation, and Connectivity
Deploy Semantic Models to Resource Groups
Administrators can configure up to three resource groups in an Oracle Analytics Cloud instance, with one semantic model deployed to each resource group. Workbook authors can access subject areas from the deployed models and use them in the Oracle Analytics workbook experience. This approach can help organizations support different departments, projects, or data domains within one Oracle Analytics Cloud instance while providing more options for organizing model deployment and capacity.
Key Takeaways
The July 2026 Oracle Analytics Cloud update provides analytics teams with additional options for reuse, flexibility, centralized management, and AI model choice. Shared calculations, filter groups, and data actions can help authors apply consistent logic across workbooks. Enhanced visualization and filtering controls can help teams tailor dashboards to specific business needs. Resource groups provide administrators with additional options for deploying semantic models. Model selection for AI Assistant and the Preview Oracle Analytics Cloud MCP Server expand the ways teams can work with supported AI capabilities and analytics content.