Oracle Fusion Middleware What's New for Oracle Analytics Desktop

Oracle® Fusion Middleware

What's New for Oracle Analytics Desktop

E76890-16

September 2019

What’s New for Oracle Analytics Desktop

Here’s an overview of the new features and enhancements we’ve added to Oracle Analytics Desktop.

September 2019
June 2019
April 2019
January 2019
September 2018
October 2017
June 2017

Release 12.2.5.4 — September 2019

Feature	Description
Oracle Analytics Desktop	Oracle Data Visualization Desktop is renamed to Oracle Analytics Desktop.
Delimiter Support	When creating a data set from a CSV or TXT file, you can specify a thousand separator and a decimal separator. When you output data from a visualization, the outputted file uses the data delimiter for your computer's locale. See Add a Spreadsheet from Your Computer and Share a Visualization or Story as a File.
Trellis Row (Y2 Axis) improvements	The default position of a visualization’s trellis row is the left side of the visualization. The formatting of the Values Axis is preserved when you change the position of the trellis row to the right side of the visualization.
Copy and Paste Between Projects	You can copy and paste a visualization or canvas from one project into another. See Copy and Paste a Visualization or Canvas.
Review Location Matches for a Map Visualization	You can review mismatch issues between data and match results in map layers, such as when there are ambiguous or partial matches between words. See Review Location Matches for a Map Visualization.
Create Custom Data Action Plug-ins	You can create custom data action plug-ins to use in Analytics Cloud. See Create Custom Data Action Plug-ins.
Font Customizations	You can customize all title and label text in a visualization. Options include font (for example, Arial), type size, and emphasis (for example, bold, underline, or color). See Adjust Visualization Properties.
Create database connections with Kerberos authentication	You can configure these database connection types to use the Kerberos network authentication protocol: Apache Hive Hortonworks Hive IBM Biginsights Hive MapR Hive Pivotal HD Hive See Create Database Connections with Kerberos Authentication.
Server-side SSL support	You can enable server-side SSL for these additional connection types: Apache Hive DB2 Hortonworks Hive IBM Biginsights Hive MapR Hive Pivotal HD Hive Spark SQL Server
Enhanced home page and search bar	Use the enhanced home page and search bar to quickly locate your analytics content. See Search for Content.

Release 12.2.5.3 — June 2019

New Features

Feature	Description
Tooltips improvement	Use the Tooltips field to adjust a visualization's tooltips content, or to turn a visualization's tooltips off. See Modify a Visualization's Tooltips.
Select alias table	You can select an alias table when creating or updating Essbase data sets. See Create Data Sets from Essbase Cubes.
Configure currency symbols	You can dynamically populate a currency symbol in visualizations based on the configured currency. See Set Currency Symbols for Visualizations.

Release 12.2.5.2 — April 2019

New Features

Feature	Description
Add notes	Add, edit, and adjust notes on a canvas. See Add Notes.
Enhanced column operations	Quickly reorganize items in the Projects, Data, and Machine Learning pages by sorting the items based on their attributes. See Sort the Items in a Page.
Data flow improvements	Employ improvements to data flows including: Transform Data in a Data Flow Schedule a Data Flow Create and Customize an Essbase Cube in a Data Flow Copy, Paste, and Skip Rules Designation Change Rules for Generation Columns
Map improvements	Employ improvements to maps in visualizations including: Create Cluster Layers on a Map Visualization Represent Point Data With Custom Icons on a Map Select Points or Area on a Map Represent Line Data Using Size and Color on a Map
Connection improvements	Create connections to the Snowflake Data Warehouse. See Create Connections to Snowflake Data Warehouse.
Specify filters for relative time periods	Display data for a specified time period based on the current date and time using the relative time filter on a Date or Date/Time column. See Apply Relative Time Filters.
Upload larger data files	Upload files with a maximum size of 250 MB. The number of data columns allowed in a single file is 250 columns. See About Adding Spreadsheets or Other Files.
Connect to on-premises databases	Visualize data in on-premises databases using the Use Remote Data Connector option. See Supported Data Sources (to find out supported remote database types, look for databases with a Y in the 'Remote Connection to Data Sets' column).

Release 12.2.5.1 — January 2019

Creating Connections

Feature	Description
Autonomous Data Warehouse connection enhancements	You can more easily create a connection to Oracle Autonomous Data Warehouse because key connection details are prepopulated from the selected client credentials zip file. See Create Connections to Oracle Autonomous Data Warehouse.
Autonomous Transaction Processing connections	You can create connections to Oracle Autonomous Transaction Processing. See Create Connections to Oracle Autonomous Transaction Processing.

Release 12.2.5.0 — September 2018

Creating and Working With Projects

Feature	Description
Preparing data	You can use data transformation and enrichment recommendations to prepare your data before visualizing it. See Preparing Your Data Set in a Project.
Visualization types	You can create Grid Heatmap, Picto, 100% Stacked Bar, Horizontal 100%, 100% Area, and Correlation Matrix visualizations.
Map layers and backgrounds	You can select a map background to use in a project. See Using Different Map Backgrounds in a Project. You can display multiple data series (different sets of dimensions and metrics) on a single map visualization in a project. See Applying Multiple Data Layers on a Single Map Visualization. You can use a heatmap as a data layer type on a map visualization to identify the density or high concentration of point values or metric values associated with the points. See Creating Heatmap Layers on a Map Visualization. You can make map backgrounds available to users. See Making Map Backgrounds Available to Users.
Inspect object properties	You can use inspectors to view and edit the properties of standalone objects in the Home, Data, Projects, and other top-level pages. See Viewing and Editing Object Properties.

Managing Data

Feature	Description
Data flow enhancements	You can branch a data flow and create multiple outputs or connections. See Branching Out a Data Flow into Multiple Connections. You can add parameter prompts to reuse a data flow across multiple sources or to use different criteria to process and select data. See Applying Parameters to a Data Flow. You can modify or select the database name, the attribute or measure, and the aggregation rules for each column of the output data set before running or executing a data flow. See Saving Output Data from a Data Flow.
Saving changes automatically	You can use the Auto Save option to automatically save your updates to a project without repeatedly clicking Save. See Saving Your Changes Automatically.
Opening objects using keyboard shortcuts	You can use keyboard shortcuts to open artifacts in a new tab or window. See Keyboard Shortcuts for Oracle Analytics.
Replacing a data set in a project	You can replace a data set by re-mapping columns used in a project to columns from a different data set. See Replacing a Data Set in a Project.
Duplicating a data set	You can duplicate an uploaded data set listed in the Data Sets page to help you further curate (organize and integrate from various sources) data in projects. See Duplicating Data Sets.

Release 12.2.4 — October 2017

Machine Learning

Feature	Description
Use machine learning to make predictions and intelligent suggestions	You can use machine learning (ML) algorithms to show patterns and uncover insights in your data sets, and then add them to your visualizations. Use the Machine Learning catalog to manage your ML scripts and models. Use data flows to train ML models using custom or built-in scripts. Use data flows to score and predict data sets using ML models. Self-service ML for diagnostics analytics of attributes (explain). Create a custom scenario for attributes by applying ML models to a data set. See Working with Machine Learning.

Feature

Description

Use machine learning to make predictions and intelligent suggestions

You can use machine learning (ML) algorithms to show patterns and uncover insights in your data sets, and then add them to your visualizations.

Use the Machine Learning catalog to manage your ML scripts and models.
Use data flows to train ML models using custom or built-in scripts.
Use data flows to score and predict data sets using ML models.
Self-service ML for diagnostics analytics of attributes (explain).
Create a custom scenario for attributes by applying ML models to a data set.

See Working with Machine Learning.

Managing Data

Feature	Description
Connect to more databases	You can connect to several new data sources: Oracle Autonomous Data Warehouse Oracle Big Data Cloud Service Oracle Talent Management Cloud See Connecting to Database Data Sources.
Data flow enhancements	Merge the rows from two data sets. See Merging Rows in a Data Flow. Create bins from a measure. See Creating a Binning Column. Use binning attributes to group your data. See Creating a Group. Use cumulative aggregate functions to group your data. See Adding Cumulative Values to a Data Flow. Calculate additional rows with forecasted values by applying a Time Series Forecast calculation. See Adding a Time Series Forecast to a Data Flow. Detect sentiment for a given text column by applying a sentiment analysis to your data flow. See Adding a Sentiment Analysis to a Data Flow. Use filters to restrict your data. See Adding Filters to a Data Flow. Transform your data using custom scripts. See Applying Custom Scripts to a Data Flow. Build data sets from a predefined sequence. See Creating a Sequence. Load data into an Essbase cube. See Creating an Essbase Cube.

Feature

Description

Connect to more databases

You can connect to several new data sources:

Oracle Autonomous Data Warehouse
Oracle Big Data Cloud Service
Oracle Talent Management Cloud

See Connecting to Database Data Sources.

Data flow enhancements

Merge the rows from two data sets. See Merging Rows in a Data Flow.
Create bins from a measure. See Creating a Binning Column.
Use binning attributes to group your data. See Creating a Group.
Use cumulative aggregate functions to group your data. See Adding Cumulative Values to a Data Flow.
Calculate additional rows with forecasted values by applying a Time Series Forecast calculation. See Adding a Time Series Forecast to a Data Flow.
Detect sentiment for a given text column by applying a sentiment analysis to your data flow. See Adding a Sentiment Analysis to a Data Flow.
Use filters to restrict your data. See Adding Filters to a Data Flow.
Transform your data using custom scripts. See Applying Custom Scripts to a Data Flow.
Build data sets from a predefined sequence. See Creating a Sequence.
Load data into an Essbase cube. See Creating an Essbase Cube.

Creating and Working With Projects

Feature	Description
Improved narration and storytelling features	When you use the improved narrate feature it makes presenting your data stories even easier. See Building Stories.
Include links to related content in your project	Enhance visualizations by offering links to related content under a handy Data Actions menu. See Working with Data Actions.
Numeric values in file-based data sources uploaded as measures	When you upload a file based data source, columns containing numeric values are imported as measures with the Number data type.
More display formatting options for numbers and dates	You can select from a wide range of number and date formats to choose the best display format for data in your visualizations. See Adjusting the Display Format of Date or Time Columns.
New properties area in the Data Panel	For quick and easy access, the properties of objects you select are displayed in the Data Panel. See Adjusting Visualization Properties.
Improved sharing	Use the to share a visualization, canvas, or story with others, as a file, by email, a printed page, and on cloud. You can also share a project or folder only in DVA format, as a file, by email, and on cloud. See Importing and Sharing.
More options to copy, paste, and duplicate	It’s often quicker to copy visualizations than starting from scratch. You can paste within the same canvas and between canvases in the same project. Use the duplicate option to make copies of an object within the same canvas or to duplicate the entire canvas. See Adjusting the Canvas Layout.
Add unrelated data sets to the same project	Your projects can contain visualizations from multiple, unrelated data sets; that is, the data sets don't have to be joined.
Date and time intelligence	You can seamlessly transition through different levels of time hierarchies or granularities with ease.
Data warning indicator	Warning signs indicate possible issues with your data. If you don't want to see any warnings in your projects you can hide them. Warnings never display in printed or shared output. See Visualization Data Warning Notification.
Background maps	Use background maps to enhance your geographical visualizations. See Enhancing Visualizations with Map Backgrounds.
Coloring maps using attribute column values	You can use color features to interpret the measure columns and attribute values in projects that include map visualizations. See Interpreting Data Measure and Attribute Values by Color in Map Visualizations.

Other Enhancements

Feature	Description
Brand new home page	Improved design that’s simple to navigate and easy to use. Personalize your home page to suit the way you want to work.
Publish a project to Oracle Analytics Cloud	You can publish a project to an instance of Oracle Analytics Cloud that is using the same version or a later version of Oracle Analytics. You can choose to include the project’s data and connection credentials. See .

Release 12.2.3 — June 2017

Creating and Managing Data Sets

Feature	Description
Connect to new data sources	New connection types are available with limited support, and are marked as Beta in the product: OData, Oracle Docs, JDBC, and ODBC.
Data Source editor	Previously you used the Data Source dialog to create or edit data sources. The Data Source dialog is replaced by the Data Source editor, which provides the same functionality but is more dynamic and easier to use. See Using the Data Source Editor.
CSV and text file delimiters	When uploading CSV and text files for data sets, you can override the auto-detected delimiter. Your choices are: Comma, Semicolon, Space, Tab, and Custom. If you select Custom, you then specify the delimiter used in your CSV file.
Subject areas as data sources	You can build data sources from Oracle Fusion Applications with Oracle Transactional Business Intelligence or Oracle BI EE subject areas. See Composing Data Sources from Subject Areas.
Data flow improvements	You can save a data flow as a database connection, which stores the data flow data to a database table. See Saving Data Flow Output Data to a Database. You can merge two or more columns in a data flow to display as one column. See Merging Columns in a Data Flow. The Data Flow editor layout is now easier to use. See Using Data Flows to Curate Data Sources.

Creating and Working With Projects

Feature	Description
Visualization types	You can create box plot, horizontal box plot, and waterfall visualizations.
Apply top or bottom N filters	You can use the top or bottom N filter to filter a measure to display a subset of its largest or smallest values. See Applying Top or Bottom N Filters.
Date and time column improvements	You can convert a text column into a true date, time, or timestamp column. See Converting Text Columns to Date or Time Columns. You can adjust the display format of a date or time column to show a different level of granularity. See Adjusting the Display Format of Date or Time Columns.
Canvas duplication and multi-canvas reordering	You can duplicate an existing canvas on a visualization and use the duplicate canvas as a starting point for a similar canvas. You can also manually reorder the sequence of multiple canvases in a visualization. See Adjusting the Canvas Layout.
Support for event data at second or millisecond grain	Line visualizations can show a continuous datetime reading on the x-axis. You can analyze data at the second or millisecond grain. Previous versions supported analyzing data at the day grain, only.
Custom map layers support	You can load and manage custom map layers in a project using geometric JSON files. See Adding Custom Map Layers.

Other Enhancements

Feature	Description
Custom Visualization Plug-in Upload	If you want to display data in a custom visualization that was created by another user or an Administrator, then you can upload and deploy the custom visualization’s plug-in to your installation. See Managing Custom Plug-ins.

Documentation Accessibility

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Access to Oracle Support

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Oracle Fusion Middleware What's New for Oracle Analytics Desktop

E76890-16

This document describes new features and other notable changes for Oracle Analytics Desktop.

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