Žiga Vaupot's Blog

Charlie Berger and Abi Giles-Haigh ran the hands-on lab session yesterday (11th May 2021) at Analytics and Data Oracle User Community's, AnDOUC ( https://analyticsanddatasummit.org/ ), TechCast Days, Spring Sessions with the title A Two-Step process for Detecting Fraud . I was invited to help with the HOLs alongside with Tim Vlamis and Edelweiss Kammermann .  The hands-on lab is about taking users through Oracle Machine Learning (SQL) Notebooks while using multiple use case scenarios for analysing insurance claims data and customer behavior data. Students were running the notebooks themselves to build and apply OML models inside Oracle Autonomous Database and then worked with Oracle APEX applications that leveraged OML’s insights and predictions ... So basically, what we did was: we took the Insurance Claims data set and ran 1-Class SVM algorithm, which is used for anomaly detection in order to identify suspicious claims.  For business (and any other) users we have an option to do

  Oracle Analytics 6.0 has arrived! Our Oracle Analytics instance was just patched a few hour ago. Everyone who is using Interactive Dashboards and Analytics (even from OBIEE times) is familiar with hierarchical columns. They are very popular with users and in some cases, like working with OLAP cubes (ie. Essbase), necessary. Oracle Data Visualisations (in the past) aka Oracle Analytics (today) lacked this functionality until now. In version 6.0 this has finally been included and here we are testing it. Data Visualisations with Hierarchical Columns Hiearchical Columns are the most applicable in tables or pivot tables, however they can be used in some other visualizations like trellis. We will create a project first. Hierarchical columns can be defined in Oracle Analytics Data Models aka Subject Areas, Oracle Planning applications or Essbase cubes. By selecting one of subject areas you can now see hierarchical columns in the data model in the Data panel: Working with hierarchical column