The March 2026 update to Oracle Analytics Cloud delivers a stronger, more guided analytics experience across visualizations, interactivity, and AI. This update introduces new controls for managing data actions and richer table and pivot experiences. It adds new ways to explore visuals with column swapping on layered charts and maps, as well as metric-based coloring for heatmaps. It also expands AI capabilities with Oracle Analytics Cloud AI Data Agents, a more conversational narrative-driven Assistant experience, and built-in AI functions in custom calculations. Updated data flow diagram layouts add new options for displaying data flows.
Featured highlights:
AI and Gen AI
- Conversational AI experience
- Oracle Analytics Cloud AI Data Agents
- Use AI functions in custom calculations
Data Visualization and Experience
- Activate data action by visualizations on the canvas
- Set data actions for parameters on buttons and charts
- Consumers add or remove columns in tables and pivot tables
- Conditional formatting with text comparison conditions
- Format gridlines in table and pivot tables
- Analyze data bars in tables and pivot tables
- Use shared images with shared layout templates
- Swap columns in maps and layered charts
- Leverage metric-basedcoloring for heatmaps
- Export all data from table and pivot as a formatted PDF
- Hide the back button in the workbook header bar
Modeling, Preparation, and Connectivity
- Data flow diagram options
AI and Gen AI
Conversational AI experience
Oracle Analytics has enhanced the conversational AI experience, pairing charts with plain-language narratives that explain what the data shows. Follow-up questions stay connected to the previous response, so users can naturally narrow the focus and keep exploring without starting over. For example, a user can ask how employee tenure varies by job title and region, then follow up with “only in North America,” and the narrative and visuals update in context, with key takeaways and recommendations that reflect the refined question.
Oracle Analytics Cloud AI Data Agents
Oracle Analytics Cloud AI Data Agents let organizations tailor the Oracle Analytics AI Assistant for consumers by pairing a specific dataset with written guidance on how to answer questions and by adding supporting documents, such as HR policy files. It’s then added to a workbook, so viewers’ questions are answered using both the data and the policy context, rather than data alone. This helps produce responses that better align with company definitions and expectations.
Use AI functions in custom calculations
Custom calculations can now include built-in AI functions, making it possible to summarize text, tag and classify records, and filter rows based on meaning rather than exact keywords. These functions can return a result for each row, create summaries across groups, or return a simple yes/no match for a natural language question.
Data Visualization and Experience
Activate data action by visualizations on the canvas
Authors can now control which data actions are available directly from a specific visualization on the canvas, so users see only the actions intended for that chart. To use it, open the workbook in edit mode, go to the visualization’s properties, and set data actions to auto, none, or custom. This keeps interactions focused and consistent by showing only the most relevant actions when a data point is selected.
Set data actions for parameters on buttons and charts
This provides the ability to set a parameter’s data actions so that it can now be tied to buttons or to clicks on a chart, allowing a single selection to change what the viewer sees across the page. For example, clicking “Bar” versus “Line,” or choosing a customer segment in a chart, updates a behind-the-scenes setting that drives which visuals appear and how other charts and tables refresh. This is a clean way to guide exploration with simple, app-like controls, without asking viewers to wade through menus or filters.
Consumers add or remove columns in tables and pivot tables
Consumers can now customize tables and pivot tables by adding or removing columns directly from the right-click context menu. Authors preselect a recommended set of columns and can offer additional options, allowing viewers can tailor the table to what they need in the moment. Any changes a viewer makes carry through when they export, so the downloaded report matches the view they created.
Conditional formatting with text comparison conditions
Conditional formatting now supports text-based comparisons, so users can highlight rows based on whether a label contains, starts with, or ends with specific words. This makes it easier to call out patterns like product brands or naming conventions, even when there are too many unique values to pick from a list. Users can also refine rules with options such as case sensitivity to avoid accidental highlights.
Format gridlines in table and pivot tables
Tables and pivot tables now allow authors to format gridlines, with options to show, remove, or customize lines for the outer border, headers, data cells, and totals. This makes reports easier to read at a glance and helps teams match familiar styles.
Data bars in tables and pivot tables
Data bars bring visuals to tables and pivot tables by showing a small bar inside each measure cell to reflect the value’s size and direction. Authors can fine-tune the look and behavior of these bars, including color, transparency, direction, and the value range, and they can choose whether the numbers appear alongside them. The result is a faster way to scan for highs and lows, compare performance, and spot trends or outliers without leaving the table.
Use shared images with shared layout templates
Shared layout templates can now retain images, such as a company logo, so branding carries over when a layout is reused. Authors can pick an image from a shared library or upload a new one, then save the canvas as a shared layout and apply it to new canvases or even set it as the default starting template. This helps teams keep a consistent, polished look across workbooks without re-adding the same images every time.
Column swapping on layered charts
Layered charts, such as overlay charts, now support column swapping, so viewers can click axis and field labels to switch what the chart shows. Authors enable the option in the chart settings and choose which dimensions and measures are available as related swap choices, including options that apply to a shared axis or to a specific layer. This makes it easy for users to explore the same visual from different angles, for example switching Sales to Profit or swapping the time scale, without duplicating charts or rebuilding the analysis.
Column swapping for maps
Maps now support column swapping, allowing users to click the map legend to switch the measure or attribute being shown without rebuilding the visualization and while keeping the same map view. This keeps the layout and styling consistent while letting users explore multiple perspectives in a single map.
Metric-based coloring for heat maps
Heat maps in Oracle Analytics can now be colored by a business metric like sales or revenue, not just by where points are most concentrated. Drop a metric on the Color field to shift the map to highlight where performance is strongest (or weakest), with simple controls to adjust intensity and how values are summarized. The result is a clearer picture of business impact by location, so leaders can spot hotspots and gaps faster.
Export all data from table and pivot as a formatted PDF
By turning on the formatted option, users can export all data from a table or pivot table as a formatted PDF. By default, the export includes only the data currently visible on screen and doesn’t retain formatting.
Hide the back button in the workbook header bar
This feature allows authors to hide the Back button in the workbook header bar. This is useful when embedding workbooks within applications because it helps authors control the user’s navigation flow by preventing users from exiting the workbook using the Back button.
Modeling, Preparation, and Connectivity
Oracle Analytics data flow diagram options
The updated data flow diagram features new node colors based on function and two layout options: compact and expanded. The compact layout reduces scrolling, while the expanded layout displays all input on the left side enhancing visibility. This allows for greater flexibility for users authoring data flows.
Key Takeaways
The March 2026 update improves data preparation with updated data flow diagram layouts that make flows easier to view and manage, and it expands AI with Oracle Analytics Cloud AI Data Agents, a more conversational Assistant experience, and new AI functions that can be used in custom calculations. On the visualization side, highlights include column swapping on layered charts and metric-based coloring for heat maps, helping users explore different angles and spot performance patterns faster without rebuilding visuals. Together, these updates help teams deliver more consistent, interactive analytics experiences and make it faster for business users to get clear answers and act on insights with confidence.