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New Features and Updates for Oracle Analytics Cloud
Oracle Analytics combines three powerful forces—augmented analytics, self-service analytics, and governed analytics. With embedded machine learning and AI, Oracle delivers a single solution that quickly scales across your organization so that you can get the most from your data. To help you get the answers you need when you need them, Oracle is committed to ongoing product innovation. Here are the latest new features and updates.
October 2019 (Release 105.4)
The Catalog make it easier to categorize the analytic assets in your system. The Home Page view on the OAC Catalog now includes all your Content from connections and data sets to reports, dashboards and visualizations. Use Natural language to search or use built-in filters to explore content by type, it will even forgive you for typos with new auto-correct abilities and recognition of plurals!
Improved logic and user interface makes it easier to work with numeric data from different locales, especially those using a variety of separators for thousands and decimal values.
Cleaning data is a reality. In this release, Data Flows has added the ability to split columns on a variety of delimiters and Prepare Data has added a built-in Trim function.
The new location matching feature helps you spot data mismatches between your data set and map layers, making it easier to ensure your visualizations are representing your data accurately.
Easily reorganize your canvases and reuse great visualizations in new or existing projects. Copy & Paste a single visualization or an entire canvas.
You asked and we delivered! The ability to customize fonts on your visualizations and canvases gives you even more control over how you present your results.
Data Action Plug-ins enable users to select data-points in visualizations and to invoke specific actions
Visualization: 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.
SSL support for Web Service and HTTP data sources has been added for Publisher.
Reporting: Publisher REST APIs
New REST APIs allow scheduling of normal & bursting operations for Publisher.
When running your reports online or via a schedule having mandatory parameters helps you ensure more useful and focused results as well as ensure successful execution by placing constraints on what is executed.
When using EPM Cloud 19.08 additional properties will be available for dimensions including the generation number, leaf indicator, member path and alias path and attribute dimensions.
Multiple new data sources are supported for use with Kerberos Authentication: Apache HIVE, Pivotal HD HIVE, MapR HIVE, Hortonworks HIVE, IBM BigInsights HIVE
Data & Security: Encrypted data sources
SSL encryption is now available for more data sources including: Apache HIVE, DB2, Hortonworks HIVE, IBM BigInsights HIVE, MapR HIVE, Pivotal HD HIVE, Spark, SQL Server
Remote Data Gateway makes it easier for users to connect to sources they frequently use by leveraging their existing desktop connectivity. RDG is now available for Impala, Spark, Apache HIVE and MySQL.
OCI Object Storage is now available for Data Replication
A redesigned page makes it easier for you to register your safe domains.
June 2019 (Release 105.3)
Language narratives bring your analyses to life, helping users who may be less familiar with your data understand the full scope and context of your analysis. New options allow you to control settings including language, level of detail, and type of narrative analysis such as trend or breakdown.
This enables you to see specific information pertaining to data points in your visualizations faster than before. Use the tooltips field to adjust the content for a visualization or to turn off tooltips. When you hover over a data point in a visualization, a tooltip displays specific information about that data point.
Need the data in your HTML pages to be as current as possible? Make sure that the data in your visualization is relevant by configuring the refresh of underlying data embedded in an HTML page.
As part of advancing support for critical Oracle Essbase functionality, we’ve added the ability to choose your alias when creating a data set from Oracle Essbase. This allows you to take advantage of enriched or translated data for your members.
You can dynamically populate a currency symbol in visualizations based on the configured currency. For example, if you set a canvas filter to display a European ledger, then the Euro symbol is displayed for each measure value that's associated with the custom currency property. The project data must contain a currency code column such as ledger currency. The currency code column enables the display of an appropriate currency symbol for the measure column, such as a profit column.
You can enable or disable the audit of reports and catalog objects. Auditing helps you track important metrics such as report starts, executions, ends, downloads, job pauses, resumes, and cancellations as well as resource creations, modifications, copies, and deletions. Selecting Enable Monitor and Audit in the server configuration page allows you to log audit data.
On Oracle Cloud Infrastructure as a Service, you can now scale up or down within the range of Oracle compute units (OCPU) for your service—without experiencing the system downtime. Scale options aren't available if you have a fixed Oracle Analytics Cloud subscription.
Governed: Redesigned Console
Improved design that’s simple to navigate and easy to use.
A redesigned page with advanced, more user-friendly settings makes it much easier to navigate and update service-level settings. Through the system settings page, administrators can set more advanced service-level options such as performance and compatibility, analysis, dashboard, pixel-perfect reporting, usage tracking, prompt, format, view, connection, and security.
This helps you plan your Oracle Analytics Cloud service, guiding you important considerations such as: Which edition do you need? Where you want to deploy your service? How many OCPUs will you need? And how many users do you expect to use the service? These are important questions because some thresholds and limits associated with publishing vary, depending on the size of your deployment.
The data gateway makes connecting to on-premises data sources easier. To get started, install data gateway into your on-premises environment on Linux, MacOS, or Microsoft Windows. Configure your on-premises environment and register one or more data gateway agents.
May 2019 (Release 105.2.3)
Manage your Oracle Analytics Cloud instances according to your safety and security needs. Pause services as needed on Oracle Cloud Infrastructure to prevent users from accessing the service. This option is available if you subscribe to Oracle Analytics Cloud through Universal Credits.
March 2019 (Release 105.2)
It is now easier to upload larger data files to provide richer insights for machine learning and artificial intelligence capabilities. You can upload files with a maximum size of 250 MB. The number of data columns allowed in a single file is 250 columns. The ability to upload larger files eliminates the risk of duplicated data resulting from splitting larger files down into smaller files.
Data flows create a collection of data derived from multiple different data sources to be used for visual analysis. Build your needed source data via data flows and draw insights from the pixel-perfect reports made within data flows from data visualization. Data flows created in the save model option and data flows with branched data sets are not supported.
The data flow editor layout is easier to use. You can save a data flow as a database connection, which stores the data flow data into a database table. You can merge two or more columns in a data flow to display as one column.
Grab your audience’s attention by adding notes. Focus on key points of the analysis that you’d like to share by adding, editing, and adjusting notes on a canvas. Refer to specific spots or data points such as column in a table, a particular horizontal bar, or a cluster in a scatter plot.
As more and more data and projects are added to your Oracle Analytics Cloud Service, it is necessary to organize your work. Now you can quickly reorganize items in the projects, data, and machine learning pages by sorting the items based on their attributes. For example, you can reorganize data sets on the data page based on their modification dates and times.
Improved map visualization makes insights for location-based data easier to convey. Improvements include creating cluster layers on a map visualization, representing point data with custom icons, selecting points or an area on a map, and representing line data using size and color.
Easily answer all of your “when” questions. Historical trends in data provide a lot of insights for future decision-making. Display data for a specified time period, based on the current date and time, using the relative time filter on a date or a date/time column.
Bring in more source data than before. This update increases the maximum number of rows you can return from any data source query or export to various file formats to 2,200,000 rows of unformatted data and 50, 000 rows of formatted data. Data row limits are dependent on the size of your service deployment, so it’s important to plan your deployment options to take advantage of this update.
Self-Service: Modify Data in Tables
Personalize reporting in dashboards and analyses. Users of a dashboard page or an analysis can modify the data they see in a table view. (Also known as writeback.)
Now you can share your insights with a larger community on LinkedIn. Share one or more of your project's visualizations, canvases, or stories to LinkedIn as a file. Create a dialogue and gain further input on your findings by sharing socially
You have freedom within a framework. For data visualization or business intelligence services deployed on Oracle Cloud Infrastructure, you can improve performance by scaling up the number of Oracle Compute units (OCPUs) allocated to your service. If your workload decreases or you need to reduce costs, you can easily scale down.
Configure your enterprise architecture and security to the service-level needs of your organization. Within the console, you can specify whether to externalize any database connections that administrators have configured for data models in Oracle Analytics Cloud or specify how often it synchronizes the database connections.
Make your operations run smoother with usage tracking. Track user queries and generate reports and visualizations to analyze the usage data. Determine which user queries are creating performance bottlenecks based on query frequency and response time. Usage tracking is monitored at the detailed user query level.
Improved connections create a richer analysis as they allow more source data to be brought in. Answer more organizational questions with more connections to data sources. Create connections to the Snowflake Data Warehouse.
Visualize data in on-premises databases using the use remote data connector option. To find out which supported data sources allow for remote connections for data sets as well as data models, click the Learn more link.
Governed: Connect to On-Premises Data Sources Much More Easily using Remote Data Connector
The remote data connector enables you to more easily connect to on-premises data to data sources. Providing remote access to more data sources improves every analytics experience. Install the remote data connector in your on-premises Linux environment using Oracle Universal Installer.
January 2019 (Release 105.1.0)
Oracle Identity Cloud Service supports multiple identity domains. Administrators can manage the identities and their rights. When setting up Oracle Analytics Cloud, you can choose between multiple identity domains to manage users and roles, integration standards, external identities, secure application integration (SSO), and Oracle Analytics authorization administration.
Migrate content faster and more easily between Oracle Analytics Cloud environments using snapshots. It doesn’t matter whether Oracle Analytics Cloud is deployed on Oracle Cloud Infrastructure or Oracle Cloud Infrastructure Classic. Downloading and/or uploading saved snapshots allows you to migrate between the two different services, between development, test, and production environments, and service deployed on Oracle Cloud Infrastructure Classic to Oracle Cloud Infrastructure.
Additional menu options in the console make migration easier. You can download a utility that exports content from Oracle Business Intelligence Enterprise Edition 11g to a migration bundle (JAR file). After exporting your content, you can upload the migration bundle to Oracle Analytics Cloud using the console.
You can capture much more when you take a snapshot. You can take a snapshot of your entire environment (everything) or specify content that you want to back up or migrate (custom). Similar options are available on restore, improving your backup, restore, and migration experience.
This utility moves data files from one Oracle Analytics Cloud environment to another. Sometimes connection issues between the source and target environment can interrupt data file migration during snapshot restore. This utility offers you an alternative way to move your data files.
You can set the configuration options required for advanced use cases through the console. Administrators can set more advanced, service-level options using the system-setting pane. Set your options to configure performance and compatibility settings between Oracle Business Intelligence Enterprise Edition and Oracle Analytics Cloud.
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. First, enable secure communication between Oracle Analytics Cloud and Oracle Autonomous Data Warehouse by uploading the trusted SSL certificates from Oracle Autonomous Data Warehouse to Oracle Analytics Cloud. Second, create a connection to Oracle Autonomous Data Warehouse.
You can create connections to Oracle Autonomous Transaction Processing to access data sources. First, to enable secure connections between Oracle Analytics Cloud and Oracle Autonomous Transaction Processing, you must upload trusted SSL certificates from Oracle Autonomous Transaction Processing to Oracle Analytics Cloud. Second, create a connection to Oracle Autonomous Transaction Processing.
View an Oracle Essbase cube and filter data for reports. You can search a dimension in a cube and include a POV parameter value in an MDX query. If you include a POV parameter in an MDX query of a data model, and if that POV parameter doesn’t exist in the data model, Oracle Business Intelligence Publisher creates that POV parameter in the data model when you save the query.
Easily pick up where you (or a colleague) left off in analysis. A snapshot is a backup file that enables you to restore your Oracle Analytics environment by capturing all or some components at a specific point in time. Migrate the credentials, configurations, and scheduled jobs of pixel-perfect reporting from one environment to another.