Q1 CY2021

1. 1.  Support for generic Java Database Connectivity (JDBC) data sources
   Extended support for the JDBC connection type lets you configure unlimited access from Oracle Analytics Cloud to other JDBC connections.
2. 2.  Connectivity to Google BigQuery
   Connect to Google BigQuery from Oracle Analytics Cloud to create live or snapshot-based datasets.

Q2 CY2021

1. 1.  Connectivity to Microsoft Azure Synapse
   Connect directly to Microsoft Azure Synapse to create live or snapshot-based datasets.
2. 2.  Support for analytics views from subject areas
   Oracle Database analytics views can be mapped into the semantic layer and consumed by every Oracle Analytics experience.

Q3 CY2021

1. 1.  Direct connector to REST APIs (JSON-based)
   The ability to use REST API endpoints as a data source for datasets will be supported. This capability lets you query existing web service URLs that provide endpoints to authorized users.

Q1 CY2021

1. 1.  Scheduled refresh for datasets
   Dataset snapshots will offer a custom refresh schedule to retrieve fresh data from data sources and applications based on a predefined and predictable schedule.
2. 2.  Introduce custom knowledge into the enrichment knowledge base
   Oracle Analytics provides the ability to recommend enrichments and transformation for various dataset columns based on built-in knowledge and a machine-learning–based data profiling engine. Custom knowledge will allow you to introduce your own enrichment sources into the knowledge system. This capability will automatically introduce these sources into the profiling engine which will generate appropriate recommendations when similar patterns are identified.
3. 3.  Advanced self-service datasets
   Expansion of the existing datasets to include multiple tables and defined join relationships as well as tables for heterogeneous sources within a single join diagram saved as a single dataset that can be shared and collaborated with across multiple users.
4. 4.  Data quality insights
   Data quality issues within datasets sometimes surface only after the data is visualized and explored. In some cases, the issues remain unseen unless specifically queried. Oracle Analytics data profiler can automatically identify quality issues and present a quality insight for each column that surfaces any possible issues. You can then fix the issues interactively and have greater confidence in your analysis.

Q2 CY2021

1. 1.  Increased limits of rows processed by data flows
   An increased limit to the number of rows that can be processed by data flows.

Q3 CY2021

1. 1.  Web-based semantic modeler
   Newly designed semantic modeler to create semantic layers on top of federated sources. With full compatibility with existing remote desktop protocols (RPDs), the new semantic modeler introduces a modern experience and focus on team development, version control, and lineage analysis.
2. 2.  Semantic model markup language
   With the introduction of the new semantic modeler, Oracle Analytics will also announce the semantic model markup language (SMML). This open, JSON-based format will allow semantic developers and third-party tools to create and modify Oracle Analytics semantics models using standard editors, codes, or scripting languages. This open format will open the possibilities for higher level of integration with homegrown and third-party applications.

Q1 CY2021

1. 1.  Support for subject area hierarchies in self-service pivot and table
   Within Oracle Analytics' self-service data exploration capabilities, you will have the ability to drill up and down predefined subject area hierarchies.
2. 2.  Charts sort dialog for custom and fine-tuned sorting
   A new surface to show the sort definition and order that is applied to a chart with the ability to modify and reorder the sorts. The dialog will also visually represent sorting issues to allow users to clearly understand the sorting logic that is applied to the chart.
3. 3.  New on-canvas filters for date and measure columns
   Expand the offering of on-canvas filter capabilities with support for specific date and measure columns.
4. 4.  Disjointed layers on maps
   Independent map layers can come from multiple data sources without the need to join these sources together. These capabilities provide power analysis in a map where your data can overlay multiple layers of geographical information.

Q2 CY2021

1. 1.  Conditional formatting
   Expansion of Oracle Analytics' self-service color management capabilities to be able to define threshold and target-based conditional formatting for every measure, and then apply it to specific visualizations as needed.
2. 2.  Flexible, layer-based combo chart
   Combo charts are a powerful tool in Oracle Analytics, offering the ability to mix different chart types into one. We will be adding more chart types that can be mixed together as well as a layer-based approach for organizing and constructing your chart.
3. 3.  Increased limits on number of rows for data export from project visualizations
   Increase row limits on various data export and download options when exporting data from Oracle Analytics projects.
4. 4.  Support for Mapbox maps and interaction
   Mapbox provides a high performance and fluid mapping experience to support even the most complex spatial scenarios.
5. 5.  High-resolution printing in data visualization
   Beautifully print your dashboards or visualizations with the WYSIWYG accuracy of your self-service analytics reports.

Q1 CY2021

1. 1.  Graph Analytics in data flows for Oracle datasets using Oracle Advanced Analytics functions of Oracle Database
   Introduce Graph Analytics functions in the DB Analytics node in Data Flows, enabling users to analyze information networks, identify paths, and other advance Graph Analytics functions.

Q2 CY2021

1. 1.  Improved natural language generation
   Creating narrative reports with natural language generation (NGL) is now even more powerful with the support of multiple attributes and measures using more inputs to generate in-depth analysis of your data. We will introduce additional data awareness to the NLG engine to generate focused insights.

Q3 CY2021

1. 1.  Automated insights
   Auto discovery of key insights based on any dataset will allow analysts to identify key behaviors in their data and quickly create collaborative stories based on these experiences.

Q1 CY2021

1. 1.  Enhanced content and in-content search with new capabilities
   Home page search just got smarter with an ability to define new search terms and fine-tune search results.

Q2 CY2021

1. 1.  Next-generation Oracle Analytics Mobile
   The next generation of Oracle Analytics Mobile will bring together all the powers of natural language, augmented analytics, and now, access to the data catalog to access any existing data visualization, dashboard, or publisher report.
2. 2.  Customize actions and options available in consumer mode
   Fine-tune the consumer experience of your projects with detailed design and user interaction options.
3. 3.  Redwood design (Preview)
   Oracle Analytics will introduce a newly envisioned Oracle Redwood design across the entire platform. Once introduced, the new design will be offered as a preview that administrator can test for themselves or turn on for their instances. Once the preview period passes, all instances will transform to the new design.

Q1 CY2021

1.  Oracle Analytics Server annual release
Oracle Analytics provides annual releases for its on-premises/self-managed version of Oracle Analytics Server (OAS). Capabilities will include all features released in OAC 5.6, 5.7, 5.8, and 5.9.

2.  OAC on Oracle Cloud Infrastructure (OCI) native health and performance-related metrics
Deliver a growing set of key health and performance metrics about each OAC instance with the customer OCI native environment.