Q3 FY2020—Delivered

1. 1.  Direct connectivity to Oracle Cloud EPM
   The new EPM direct connector allows self-service users to create a connection to Cloud EPM, without having to create a subject area.
2. 2.  New metadata for Cloud EPM: Hierarchy generations
   Connecting to Cloud EPM using the new direct connector or via a subject area offers generation columns for hierarchies similar to those already available for Essbase sources. Generation columns include coverage for member names and aliases.
3. 3.  Microsoft Azure SQL Database certification
   The ability to use Microsoft SQL Server data direct connector and remote data gateway with Azure SQL Databases.

Q4 FY2020

1. 1.  Java Database Connectivity (JDBC) driver for accessing Oracle Analytics Cloud
   Ability to connect and query Oracle Analytics Cloud data models and data sets using a JDBC driver.
2. 2.  Remote data gateway support for accessing Essbase via a subject area
   Extend the remote data gateway support for Oracle Essbase to enable secured access to on-premises Essbase deployments via subject areas.
3. 3.  Access Oracle Fusion Applications from Oracle Analytics Publisher
   Connect to Fusion Applications from Oracle Analytics Publisher. You can additionally use the data source in data models you create.
4. 4.  Remote data gateway support for Oracle MySQL Database
   Access on-premises MySQL databases using remote data gateway.

Q1 FY2021

1. 1.  Support for generic 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 data models. Also enables you to create data sets.

Q3 FY2020

1. 1.  Simplify the data set editor: Delivered
   Simplify and reduce the steps required to create a data set. Business analysts can now complete all the data set editor existing and new tasks in a single page.
2. 2.  Support for regular expressions (Regex) in the replace tool within data prep
   Support for Regular Expressions (Regex) within the Replace tool in Data Prep provides the ability to do sophisticated search and replace operations across Data Set values.

Q4 FY2020

1. 1.  Scheduled refresh for data sets
   Data set 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.  Advanced self-service data sets: Preview
   Expansion of the existing data sets to include multiple tables and defined join relationships as well as tables for heterogeneous sources within a single join diagram saved as a single data set that can be shared and collaborated with across multiple users.
3. 3.  Introduce custom knowledge into the enrichment knowledge base
   Oracle Analytics provides the ability to recommend enrichments and transformation for various data set 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.

Q1 FY2021

1. 1.  Data quality insights
   Data quality issues within data sets 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.
2. 2.  Advanced self-service data sets
   Expansion of the existing data sets to include multiple tables and defined join relationships as well as tables for heterogeneous sources within a single join diagram saved as a single data set that can be shared and collaborated with across multiple users.

Q3 FY2020—Delivered

1. 1.  Placed customized filters on the canvas
   Create beautiful dashboards with full control of filter placement inside your canvas. You can now provide your consumers with the ability to access on-canvas filters for a more simplified analytics experience.
2. 2.  Digitized custom map layers—create interactive visualizations from any image
   Easily create custom, interactive visuals from any image. You can upload images, define relationships between image areas to data values using a no-code design tool, and use these images either as interactive visualizations or filter experiences.
3. 3.  Pivot/table flexible and persistent cell sizing
   Present your pivot tables with clarity. You can now control the column/row size within the pivot and table visualizations to fine-tune the experience to fit the data and your visual goal.
4. 4.  Add a spark chart to any tile visualization
   Performance tiles are an important visualization in many dashboards, but sometimes there is a need for more data to tell a full story. Oracle Analytics’ performance tiles now include spark charts (mini charts) to display more data, such as trends.
5. 5.  Waterfall chart enhancements
   Increasing the flexibility and scope of Oracle Analytics’ visualization capabilities is a key part of every release. For Q3 FY2020, we focused on improving the usability and applicability of waterfall charts in many use cases. With this set of improvements, you will be able to control various aspects of your chart, such as color setting for the start/end and increase/decrease bars. You will also be able to specify unique colors for a specific data bar that help identify key data points.
6. 6.  Enable top/bottom N filters for attribute filter
   In addition to the top/bottom filter type for measures, we added a similar capability of top/bottom N for attribute filters. These advanced filter capabilities bring simplicity and power to analysts.
7. 7.  Disable map gestures
   In some cases, you may not want to allow users to navigate around the map on your dashboard. This capability will allow you to disable integrative gestures on the map and leave the geo navigation to the data.
8. 8.  Improved map rendering and interaction performance
   Rendering large maps with thousands of data points just got better, with increased speed and scale.

Q4 FY2020

1. 1.  Support for subject area hierarchies in self-service pivot and table: Preview
   Within Oracle Analytics' self-service data exploration capabilities, you will have the ability to drill up and down predefined subject area hierarchies.

Q1 FY2021

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.  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.

Q2 FY2021

1. 1.  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.
2. 2.  Support for Mapbox maps and interaction
   Mapbox provides a high performance and fluid mapping experience to support even the most complex spatial scenarios.

Q3 FY2020—Delivered

1. 1. Register and consume Oracle Machine Learning models in data flows
   Machine learning models often exist in different platforms, which makes it hard for them to be used and consumed by business analysts. With this capability, you will be able to register machine learning models stored in Oracle Machine Learning in Oracle Analytics and use those models for predictive analysis within data flows. This leverages the database scale and performance as the execution layer, reducing data movement and increasing performance at scale.
2. 2. Oracle Advanced Analytics functions in data flows
   Data flows will be able to use the Oracle Database unsupervised advanced analytics functions, such as dynamic clustering, regression, classification, and feature extraction, while function shipping the execution to the database layer.
3. 3. Improved and fine-tuned forecast data quality
   New capabilities that improve and optimize the algorithms used for one-click forecasting enhance the quality of the data you use for analysis.
4. 4. Additional output details for machine learning training data flows
   Machine learning training process output includes additional information about the training process and the resulting models for improved, explainable AI capabilities.

Q4 FY2020

1. 1. Unpivot columns to rows in data flows for Oracle data sets using Oracle Advanced Analytics functions
   Support for the Oracle Database unsupervised Advanced Analytics function for quickly unpivoting data as part of the data preparation process.
2. 2. Sample data in data flows for Oracle data sets using Oracle Advanced Analytics functions: Delivered
   Support for the Oracle Database unsupervised Advanced Analytics function for smart sampling of data to be used for machine learning training and other purposes where a representative subset of data is required.

Q1 FY2021

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 FY2020—Delivered

1. 1.  Responsive canvas layouts
   More dashboard design options will be added to allow responsive growth of the canvas on both axes based on author content and adaptation to different screen resolutions.
2. 2.  Administrator ability to push content into Day by Day feeds for suggested viewing
   Create your own ‘suggested viewing’ insights or proactive content publishing into Oracle Analytics Cloud Day by Day. The new administrator capability allows you to seed Day by Day feeds for all or some users.
3. 3.  Improved visibility and usability of the canvas bar
   Creating a project means you will have many different canvases that you create and need to navigate. The improved content density of canvas names provides better visibility and quick duplication of a canvas for iterative report creation and testing.
4. 4.  Duplicate/copy canvas to appear after the targeted canvas
   While duplicating or copying canvas tabs, new canvases now appear next to the original (instead of at the end of the list) for ease of accessibility.
5. 5.  Improved system setting interface
   The system setting interface is streamlined for faster navigation.

Q4 FY2020

1. 1.  Allow charts to regain title area if title is hidden: Delivered
   Get the most out of the chart area by regaining white space when you choose not to use certain chart elements, such as the title.
2. 2.  Copy/duplicate my calculations: Delivered
   Developers can quickly copy and duplicate custom calculations for faster calculation creation for derivates of calculations, backup copies, or testing of syntax scenarios.
3. 3.  Copy my calculations expressions to the clipboard: Delivered
   This enhancement enables you to save time by having the ability to copy an entire expression to the clipboard without opening the formula editor.
4. 4.  Allow for simple presentation creation
   Presentation mode for your projects will be automatically created, saving you the initial creation time, and enabling you to focus on customization and organization.

Q1 FY2021

1. 1.  Customize actions and options available in consumer mode
   Fine-tune the consumer experience of your projects with detailed design and user interaction options.

Q3 FY2020

1. 1.  Oracle Analytics Server for Windows
   Support for installations of Oracle Analytics Server on the Windows operating system.
2. 2.  Support Microsoft SQL Server as an Oracle Analytics Server repository
   Support for SQL Server as a repository database for Oracle Analytics Server.
3. 3.  Access Oracle Analytics Cloud via a private IP
   Assign and use a restricted private endpoint for your organization’s Oracle Analytics Cloud instance.

Q4 FY2020

4. 1.  Access remote sources via VPN
   In addition to the existing ability to access your remote data sources using remote data gateway, you will be able to use direct access to these sources within a virtual private network (VPN).