Virtual Columns in Oracle are a convenient feature to implement derived measures of a fact table. But in combination with Oracle Database In-Memory, it has an impact on performance – unless you use Oracle 12c Release 2.
Loading data into a Data Vault Model is easy. But how complex is it to extract the data from a Data Vault into a dimensional Data Mart? A Point in Time (PIT) table helps to load Dimensions from a Hub with multiple Satellites.
In my last blog post, I noticed that surrogate keys on a time dimension cannot be combined with partitioned fact tables in a star schema. Actually, there is a way to do that: With reference partitioning it is possible to implement monthly partitioned fact tables based on a surrogate time key. But is this a good idea?
In the physical design of a star schema, it is recommended to use surrogate keys for the primary keys of dimension tables. Except for the time dimension. In Oracle data warehouses it is common to use a DATE column as the primary key. The reason for this decision and several alternative solutions are described in this post.
The Oracle OpenWorld 2014 just finished yesterday, but unfortunately I was not able to attend this great conference this year. Perhaps next year – who knows…
But I had the luck to give several presentations in the last few years on Oracle OpenWorld in San Francisco, on the DOAG Conference in Nuremberg and on some other German conferences. Now you can find all these presentations on SlideShare. Because most of the slides are not brand new, my Trivadis colleague Silvana Bernasconi reformatted the older presentations to the current Trivadis PowerPoint template (thank you, Silvana). Nevertheless I promise: The contents of all these presentations is still up to date. Enjoy to have a look at and probably download some of the presentations.
An overview of all my presentations you can find on the Presentation page.
…does not exist. Each Data Warehouse is different. Not only the known (or unknown) analytical requirements and the number, complexity and structure of the source systems have an impact on the architecture and design of a Data Warehouse.