Oracle Analytics Cloud and Server Roadmap

H1 2022

• 1. Filter based on invalid data in quality insights
  Quality Insights provides clear statistics about the validity of a column values. With this update, you will be able to interact with the insight to filter column values based on their validity or invalidity.

• 2. Files in datasets with multiple tables
  Datasets can now include content from relational sources, Oracle Applications, and uploaded files such as Microsoft Excel or CSV files.The dataset author sets the joins and presentation experience of the datasets, allowing greater control over dataset data models and clear SQL-like semantics for join behavior. Advantages to this include simplified joining of relational datasets to files and better management of dataset elements.

• 3. Public REST API framework and API for Snapshot creation and restore
  Administrators can automate the creation and restoration of snapshots via an API. This is the first in a series of APIs which will automate key administrative tasks, many of which are manual today. The snapshots are stored in a customer-controlled Oracle Object Storage bucket, which makes management and reuse of snapshots straightforward.

• 4. Microsoft Power BI connector
  This Oracle-developed Microsoft Power BI connector will enable you to access Oracle Analytics Cloud and use its industry-leading, enterprise-class semantic model to create Power BI reports.

• 5. Oracle Analytics Publisher support for Snowflake databases
  Oracle Analytics Publisher will allow you to create pixel-perfect reports using Snowflake as a data source.

H2 2022

• 1. Direct connector to REST APIs (JSON-based)
  This new self-service connector means you can connect generically to REST API endpoints to create datasets. This capability allows you to develop workbooks and visualizations sourced from a variety of SaaS systems that are accessible via REST APIs.

• 2. Web-based semantic modeler
  A newly designed, fully browser-based semantic modeler enables you to create semantic layers on top of federated data sources. Fully compatible with existing enterprise data models that use relational sources in repository document format (RPD), the new semantic modeler introduces a modern experience which focuses on team development, version control, and lineage analysis.This new tool is based on Semantic Model Markup Language (SMML) and stores all authoring as source code.You can use the integrated source control or integrate directly with any Git-compatible Repo such as GitHub, GitLab, or Git on OCI.

  With full support for branching and merging, multiuser development becomes simpler and easier.With SMML, developers can use the tool to make changes directly in the source or with the integrated JSON editor.With Git integration, you have full visibility to a complete change history.The ability to publish to multiple targets also simplifies reuse.

• 3. Semantic model markup language
  With the introduction of the new semantic modeler, Oracle Analytics will also announce the Semantic Model Markup Language. 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, and scripting languages. This open format will expand the possibilities for a higher level of integration with homegrown and third-party applications.

H1 2022

• 1. Control the radius of the donut hole in the donut charts
  In a donut chart, you will now be able control the radius of the donut hole. This helps manage data display and improve presentation.

• 2. Change settings for multiple columns in a dataset
  This update improves bulk editing and saves you time when changing settings for multiple columns. You will be able to multi-select columns in the metadata view to change the data type, the treat as setting, the aggregation Type, and the Hide setting for more than one column at once.

• 3. Conditional formatting for performance tiles
  We continue to expand conditional formatting across the platform.This update allows you to define conditional formatting for performance tiles.

• 4. Open workbooks as a viewer
  Authors will be able to open workbooks as a viewer by default, and they will also have the ability to jump directly into editing mode if needed.

• 5. Customizable consumer navigation
  With this feature, authors have a new bottom tabs presentation style that provides more control when curating the consumer navigation experience. Authors can choose this style from the presentation property panel.

• 6. Author-controlled dashboard filter bar
  This enhancement to the dashboard filter list box offers multiple filter options in the same control.So instead of putting six list boxes on your screen, you will manage a single filter bar with drop-down selections.

H2 2022

• 1. Customized actions for consumers
  This update allows authors to define which options are available for a consumer.For example, an author can give users access to a workbook as consumers, but restrict their ability to drill down.

• 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. User control for My Calculations properties
  With this update, you will be able change the behavior of attributes and measures in My Calculations.

• 4. Export to Microsoft Excel
  You can already export data to a CSV file. This update goes a step further by enabling you to download data directly in the Microsoft Excel format, saving time and effort.

• 5. Key metrics semantics
  This capability helps identify metadata about key metrics, such as which measures are important in your KPI and which other measures are related.It will be visible first in workbooks.

• 6. Insights watchlist on the homepage
  The watch list will give you the ability to track information and visualizations that are important to you on your homepage.

• 7. Geospatial data types support and project geometry shapes
  This update enables OAC to natively consume geometry data types in any dataset. Geometry data types are a binary format that defines a shape on a geographical map. Columns containing geometry data types will become natively projectable on a map. This new feature can be used to support specific spatial calculations, such as the distance between two points on a map.

H1 2022

• 1. Streamlined Advanced Analytics for unsupported sources
  In certain circumstances for Oracle Enterprise Performance Management (EPM) and Essbase datasets, one-click advanced analytics capabilities may not produce the expected results. To avoid any confusion, one-click analytics will no longer be available for these datasets.

• 2. Additional algorithms integrated with Oracle Machine Learning: XGBoost and Neural Network
  OAC will now allow users to register and apply additional Oracle Machine Learning model types, including XGBoost and Neural Network algorithms.

• 3. Datasets automated insights
  Automatic discovery of key insights based on any dataset will allow analysts to identify important insights in their data and quickly create collaborative stories.

• 4. Oracle Functions integration for OAC Data Flows
  This is a secure framework for extending analytics. Users will be able to register an API call or custom script as a function.For example, say you want to execute a dataflow that runs a custom Python script,now you can upload the script to OCI Compute and define a function for it. OAC consumes the function, running the script from OCI Compute, safely and securely.

H2 2022

• 1. Integration with Oracle Cloud Infrastructure AI Services – OCI Language
  This update introduces an integration with Oracle Cloud Infrastructure Language, a service that allows customers to uncover insights in unstructured text using natural language processing. Key capabilities of OCI Language include language detection, sentiment analysis, text classification, named-entity recognition, and key phrase detection.

• 2. Integration with Oracle Cloud Infrastructure AI Services – OCI Vision
  This update introduces an integration with OCI Vision, a service that allows customers to uncover insights from within images. Key capabilities of OCI Vision AI include object detection and text detection and classification, allowing analysts to quickly make sense of image-based content.

• 3. Advanced Explain algorithms and improved user experience
  These updates to the Explain feature will include improving the interface, improving algorithms (such as segmentation), and more controls for managing the user experience.

H1 2022

• 1. Administrator governance of self-service assets
  This will enable administrators to manage assets in personal catalog directories so they can transfer ownership among users and identify data security concerns. It includes granting/revoking access, copying/pasting to other locations, and modifying properties.

H2 2022

• 1. Service administration console email formats
  Within the OCI service administration console, you will be able to add more configuration options for email delivery via agents. These additional options will enable you to support a multi-byte Outlook format, show the recipients in the email, restrict emails to certain domains, and more.