As a user of Oracle Analytics Cloud, you already have access to one-click visualizations and reports. These self-service analytics make it easy to quickly handle data preparation, discovery, and visualization for users of all kinds: business users, citizen data scientists, managers, and other people without the in-depth training of a professional data scientist. In fact, that’s one of the true benefits of Oracle Analytics Cloud: its intuitive user interface allows anyone to discover, visualize, and manipulate data in cutting-edge ways.
But what about upstream of all that data? Have you ever wondered what data scientists using Oracle Autonomous Database with Oracle Machine Learning are capable of? As they build custom machine learning algorithms and models, their ability to derive further insights or work with more specifically targeted elements of data goes far beyond what business users can do.
A good analogy of this comes from cooking. You may enjoy food, maybe even know how to cook a little, and you know what appeals to a discerning palette. But you simply don’t have the professional training to know exactly what ingredients and cooking techniques to use to make a truly custom gourmet meal. That’s the difference between a business user of Oracle Analytics Cloud and a data scientist building models and algorithms with Oracle Autonomous Database.
But what if you could have that knowledge and expertise on demand? Or, to use our cooking analogy, have every amazing custom gourmet meal available to you just like selecting dishes from a menu? With Oracle Analytics Cloud’s 5.7 release, any custom models or Oracle Machine Learning algorithms built in Oracle Autonomous Data Warehouse and Oracle Database are now available at the touch of a button to business users of Oracle Analytics Cloud.
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By enabling access to Oracle Machine Learning models and algorithms built in Oracle Autonomous Database, users experience a democratized version of data science. Specifically, this enables two functions designed to let Oracle Analytics Cloud users take advantage of materials built at the database level:
Machine learning models from Oracle Autonomous Database can now be registered in Oracle Analytics Cloud. Upon registration, these can be applied to datasets and data connections through the Oracle Analytics Cloud interface. Not only does this reduce the cost of switching between environments, it opens the door for business users to tap into the expertise of an organization’s data scientists.
Analytic operations within Oracle Autonomous Database can now be leveraged. With the 5.7 release, four new operations from Oracle’s database products are available, with more to be added in future releases. This reduces data movement for a streamlined analytics experience across environments—ultimately powering a greater level of self-service data discovery.
In addition, the 5.7 release simplifies the user interface to accelerate self-service analytics. New top/bottom filters enable a better focus on key drivers without the need to create complex formulas. Several new visualizations are available, including Spark Chart in Performance Tiles and Waterfall Bridge. The 5.7 release also provides on-canvas filters for greater control over interactions, along with the option to display results in a new responsive canvas layout.
For all of the updates in Oracle Analytics Cloud 5.7, see the complete list in What’s New in Oracle Analytics Cloud as well as the upcoming product roadmap. And to learn how you can benefit from Oracle Analytics, visit Oracle.com/analytics, and follow us on Twitter @OracleAnalytics.