Working with Data Catalog in Oracle Data Lakehouse

Oracle Cloud Infrastructure (OCI) Data Catalog is part of Oracle Data Lakehouse platform and is defined as "a fully managed, self-service, data discovery and governance solution for your enterprise data. With Data Catalog, you get a single collaborative environment to manage technical, business, and operational metadata." ( ) I am sure many of users will find Data Catalog very useful. It provides several really nice features which enable users to: harvest metadata from various data sources, create a common, enterprise-wide business glossary, link data to business terms and tags, explore data assets in data catalog, automate harvesting jobs to update the catalog on regular basis, integrate with other applications using REST APIs and SDK. So where do we start? At the beginning, of course. We need to locate Data Catalog Service in OCI.  It is located under Analytics & AI menu item in OCI navigation panel and then y

Oracle Analytics: March 2022 Update

Oracle Analytics, March 2022 Update is available! … and as usual is bringing some new exiting features. I will focus on some really nice one, three to be exact, which I was waiting for quite a some time and which will definitely improve developer and end user experience: new content management tool conditional formatting in Performance Tile visualisations Dashboard Filter Bar Content Management Personally, I am missing some more content management tools in Oracle Analytics. In this, March 2022 Update, this is certainly improving. Under the Console  users have now an option to use  Content  management tools.  Content management allows user quickly search through all objects (not just catalog) in the system. It allows searching by owner as well. Of course, more details are always available to inspect: If use is Administrator, she can transfer ownership of an object from one user to another. Example being, an employee leaves company.  This functionality in general is not new. It was avail

Training and deploying AutoML models in Oracle Data Lakehouse

  Oracle Data Lakehouse Series highlights some of the examples of using elements of Oracle Data Lakehouse and presents the tools that are available as part of Oracle Cloud Infrastructure. The first blog, Using OCI Object Storage based Raw Data in Oracle Analytics , of the Series talks about how to use Object Storage for “a file cabinet” for the retail transactions CSV files. These files are then “registered” with Oracle autonomous database and used in Oracle Analytics analyses. Any new files added to that “file cabinet” are immediately included in any analysis. Of course, there are several ways to perform the following exercise, but in this 2nd example I’m discussing similar approach to load and use the data, however there are two add-ins in the process. Firstly, we will use Oracle Analytics Data Flows to prepare data for machine learning exercise and secondly we will use Oracle Machine Learning AutoML feature to build a prediction model which will be registered with and used in Oracl