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The latest Oracle Analytics news, product updates, customer and partner stories, and market insights.

Explore New Features in Oracle Analytics Cloud Release 6.0

Oracle Analytics Cloud (OAC) Release 6.0 introduces sophisticated new capabilities that expand access to analytics and accelerate your time to insights, such as Oracle machine learning and database and graph analytics.  You’ll appreciate new features that help you quickly assess the state of your data, along with expanded data set capabilities that enable you to combine multiple sources with full join control in an easy user interface.  There’s also new data connectivity you can leverage for Google BigQuery and JDBC. 

What’s New in Release 6.0 

Oracle Machine Learning

Database Analytics

Support for Database Analytics Association Rules in Data Flows | Docs

Frequent itemset, as released in Oracle Analytics 5.9, enables you to see groups of products commonly purchased together.  You can now generate association rules for these groupings which indicate that for certain groups of products, what additional product is brought.  For example you can understand, based on buying behavior, if a customer normally buys bread and milk that they also purchase eggs.

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Support for Database Analytics Time Series in Data Flows | Docs

Use the Oracle machine learning model's rich controls for choosing the model type and parameters when you forecast data. You can generate time-series statistics to evaluate the accuracy of your model.

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Graph Analytics

Shortest Path | Docs

Oracle Analytics now provides users with a simplified user interface to access graph data from Oracle Autonomous Data Warehouse to calculate the shortest path from a source to a destination.    This type of information is extremely valuable for a business that creates transportation routes or needs to ensure efficiencies when traveling between two locations.

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Sub Network | Docs

You can use sub-network graph analytics to utilize relationship data. Ever wonder how social media platforms show you how many immediate contacts you have versus second or third connections? This capability enables you to quickly determine how many hops away your relationships are.

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Node Ranking | Docs

Ranking is commonly used in web search engines to determine the best results to display first in a list.  If a certain webpage has many other pages that direct traffic to it, this page ranks higher in the analysis than a single page that isn’t reached through other web pages. 

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Nodes Clusters | Docs

Clustering using graph analytics groups connected relationships into a cluster that has a relationship in both directions between the source and destination.  When the relationship between two vertices doesn’t go in both directions, these points reside in separate clusters.

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Data Preparation and Connections

Data Preparation
Data Sets with Multiple Tables | Docs

There are new advanced data modeling capabilities for self-service data modelers. You can now work with data sets that utilize multiple tables from heterogeneous sources with defined join relationships. This uses a single join diagram saved as a single data set. You can define cardinality between joins to ensure your data is aggregated accurately. 

  • Join type control
  • Table pruning creates efficiencies in your queries so if there are 10 joined tables in your data set but only 2 tables are used, the query only uses the two joins
  • Scheduled data set refresh
  • Collaborate across multiple users
  • Sources can be both live and static

Video series: Part 1 , Part 2, Part 3, Part 4, Part 5

Data Quality Insights | Docs

Whether you’re importing data from files or connecting to existing sources, Quality Insights accelerates getting your data ready for analysis.   Leveraging the power of the semantic profiler in Oracle Analytics, Quality Insights provides a visual representation of your data's quality, helping you rapidly identify issues.  These indicators are based on null values, data type inconsistencies, and semantic type classifications.  Each column in your data has a graph to show the distribution of the represented data.  You can make inline edits to quickly address any issues, rename columns, and use the scrollable mini map to easily traverse long lists.

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Custom Knowledge | Docs

Every business has standard metadata that applies to them.  Administrators can now import this information into the Reference Knowledge section of the console for all users to leverage.  The semantic profiler in Oracle Analytics will incorporate both the system knowledge that exists today and the business metadata that’s added to the enrichment recommendations, increasing accuracy and providing better context during data preparation.

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Data Sources

Connect to JDBC Data Sources | Docs

JDBC connectivity opens up a wealth of sources to you.   Using Remote Data Gateway (RDG), you can configure the JDBC drivers to allow Oracle Analytics to connect to data sources for cached data.   This connection type supports data sets with multiple connections so you can easily integrate this data with other data in your business.

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Connect to Google BigQuery | Docs

Create connections to your Google BigQuery sources, natively through self-service analytics.  Users can create and configure these connections to reach the data they need quickly.

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Scheduled Data Set Reload | Docs

Data sets may not always need to be static or live and manually refreshing them can take time.  Now you can configure your data sets to be refreshed based on a static date and time or set repeat schedules to occur based on your needs. 

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Data Visualizations and Design

Hierarchy Navigation in Self Service | Docs

Traverse your data like never before with support for hierarchy navigation of your subject areas or multidimensional sources such as Essbase or EPM.  Defined hierarchies are now displayed in the self-service data navigation panel allowing you to drill up and down into your pivot or table visualizations.   Unbalanced, ragged, and parent-child hierarchies are all supported.

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Weighted Average in Waterfall Visualizations | Docs
Waterfall visualizations continue to evolve in Oracle Analytics.  With this release, you can use weighted averages as a value in the grammar panel.  This enables you to display the variation between the categorical values represented on the x-axis.  In some cases, this shows a better representation with a percentage change as compared to a discrete value change.

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Map Layers with Non-joined Data Sets | Docs

Geospatial analysis is a powerful tool to visualize geographic data.  Many times, you’ll have unrelated data sets that you want to compare on the same map.  With non-joined data sets, you can overlay unrelated map data and see how the points correlate to each other.

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Other notable features include:

  1. Canvas Auto-Refresh enables users to schedule the automatic refreshing of their dashboards via the canvas properties.
  2. On-Canvas filter enhancements include filter types, date filters, and measure filters.
  3. Visual Experience enhancements include the custom sort order dialog, export, and title tooltip.
  4. Improved Home Page Search allows for advanced search commands.
  5. OA Publisher Leveraging OCI Object Storage to store your publisher objects.

 

 

 

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