Oracle Analytics Cloud embraced ML/AI as a foundational strategy years ago, and it just keeps getting better!
In this blog you’ll find 5 great reasons to choose Oracle Analytics Cloud (OAC) from an ML/AI perspective.
1. Embedded Machine Learning is key and makes ML easy with OAC.
No need to be a guru in Machine Learning to start using ML algorithms. Oracle Analytics Cloud provides an easy, intuitive click-through experience to help you in your prediction tasks, whether you’re predicting revenue in the next months or predicting which customers are most likely to adopt an offer. Most of the time you don’t need a data scientist to build a complex machine learning model for your inquiries – OAC helps you get fast, accurate answers.
Get things moving with the embedded Machine Learning algorithms that are just a couple of clicks away, as part of the Data Flow functionality. You have several algorithms at hand for the main types of machine learning tasks: Numerical Prediction, Binary and Multi Classification, as well as Clustering. For datasets in Oracle Autonomous Database, it adds one extra flavor: AutoML. The AutoML data flow step chooses the best algorithm from the supported ones and identifies the features and tuning to employ for the best performance.
2. Graph Analytics for Oracle Database.
Perform geospatial analyseson Oracle Database and Oracle Autonomous Data Warehouse data sources and find the shortest path, node ranks, subgraphs or clusters, all in a drag and drop approach with data flows and the Graph Network plugin.
3. Data Scientists can work directly in OAC.
Break up the silos between analytics and data science teams. Promote collaboration and reuse machine learning models created by your data scientists in Oracle Machine Learning or Oracle Data Science. Register them in OAC and apply them as you would any other model in the data flow. Check this video to see how you can register and invoke OCI Data Science Models.
In addition, Oracle Analytics Cloud provides explainability to Oracle Machine Learning Models, giving you the advantage of a complete, enterprise-ready cloud platform to help connect the dots and be more effective.
4. AI is the trend – and OAC is on top of it.
AI is embedded everywhere in Oracle Analytics Cloud. Use Natural Language Query to ask questions on your data, in one of the 28 supported languages, directly on OAC’s home search bar. Relevant visuals will be displayed immediately as part of the answer to your query.
Have a look at the dataset’s Auto Insights when starting an analysis. The generated visuals are a good starting point for your work. Try filtering the attributes and type of visualizations in Auto Insight’s settings, so they are even more relevant to what you are looking for.
Use the Explain feature to find more on a target variable. Want to know the drivers of revenue? Or understand more about churn? Just right-click on the specific attribute or measure and choose Explain. You’ll get a report that mixes auto-generated visuals with natural language generated text explaining basic facts about your target, as well as the key drivers, clusters and anomalies in your data with respect to the specific target.
And speaking of Natural Language Generation, the Language Narrative visualization creates natural language descriptions of the attributes and measures in your dataset, in a trend or breakdown approach, with a customized Level of Detail.
Not to mention that Oracle Analytics Cloud has the best data storytelling capabilities, according to Gartner, offering auto-generated podcasts with AI avatars. Read an entire blog post on this topic here.
5. AI models at your fingertips.
Use OCI Vision, either pretrained or custom models, for object detection, image classification and text detection. Create the most visual dashboards on top of the output – and here there are 2 custom visuals to support that: AI Vision Series to help in illustrating the detected objects and Image Gallery, to help you through the gallery of analyzed images.
Plain text is not to be discarded anymore – in fact, it’s the new star in analytics. Use OCI AI Language pretrained models to detect language, identify key phrases and named entities, classify text, and analyze sentiment in your documents, including customer reviews or complaints, emails, social media content and more. The Text Highlighter visualization extension can be of great help when displaying the insights.
Want to try it yourself? Here’s a hands-on lab using OCI AI Language Service and OAC that you can try for sentiment analysis right now!
The November release adds one extra flavour: OCI Pretrained Document Understanding models are now seamlessly integrated with OAC, to perform document classification and key value extraction without the need of machine learning or artificial intelligence expertise. The key-value extraction models help extracting information from driver licences, passports, receipts, and invoices, opening doors to a variety of new usecases.
These are only 5 of the many reasons to try out Oracle Analytics Cloud. And as announced in the recent Oracle CloudWorld, there’s even more to come. You’ll soon experience Generative AI Data Interactions and enhanced augmented analytics. Read more in the announcement here.
So what now?
This is the time to move from traditional BI dashboards to modern analytics dashboards, that leverage Artificial Intelligence and Machine Learning and provide autonomy to business users through self-service analytics. Oracle Analytics Cloud is the platform that will support you in this journey, providing everything you need for modern analytics, in an enterprise scalable, secure environment.
And I simply cannot resist not to point to Larry’s Ellison keynote in Oracle CloudWorld this year, speaking on Oracle’s vision for the future and how AI plays a big part of it.
Hope all these possibilities have gotten you excited to try AI and Analytics for yourself, and look forward to seeing your thoughts in the Oracle Analytics Community site!
