Žiga Vaupot's Blog

Using AutoML in Oracle Analytics Approximately one year ago, I have written a blog post Training and deploying AutoML models in Oracle Data Lakehouse . This blog post was part of my Oracle Data Lakehouse blog series, was focusing on training and deploying AutoML models in Oracle Autonomous Data Warehouse (ADW). Besides that, the post was also focusing on storing and managing data files in object storage and registering them as external tables in ADW. AutoML generated models are stored and deployed in ADW as any other OML models. If you want to use these models in Oracle Analytics you have to manually register OML model with Oracle Analytics and use it. There is a small detail regarding the location of data to be used with such a model - data has to reside in the same database where model is deployed. Not to mention, that user has to log into OML Notebooks in ADW and perform the training there. In the latest, March 2023 Update, release this is no longer needed as Oracle Analytics

This blog post has been prepared and written in cooperation with Joel Acha , Oracle ACE Associate & Senior Business Solution Architect at Qubix Intl. Parameters in Oracle Analytics The use of parameters in OBIEE (the predecessor of Oracle Analytics ) is a feature that made it possible to add session personalisation to the user experience. This feature has been missing in Data Visualisation workbooks until now. The March 2023 Oracle Analytics Cloud update has a few product updates but the most prominent new feature of this update is undoubtedly the introduction of parameters to Data Visualisation workbooks. About Variables in Oracle Business Intelligence (OBIEE) We’ll start things off by taking a look at what functionality existed in OBIEE . There are several variable types that could be used to pass static or dynamic values. Session Variables are assigned a value when the user signs in to Oracle Analytics and their values persist for the duration of the user session. Th