Rittman Mead - Delivered Intelligence

Hopefully you’ve read the introduction, Part 1, and Part 2. Those posts detailed methods for building fault-tolerant ETL code, with a strong bias in favor of using Oracle Database features. Now I’ll drill into the backup and recovery aspect of data warehousing fault tolerance, and tackle the age-old question of whether to ARCHIVELOG or NOARCHIVELOG [...]

In my last post, I described the First “R” in data warehouse fault tolerance: Resuming. As I mentioned in the introduction to this series, my goal is a triage approach where the simple things, such as space errors, are handled effortlessly without repercussions. But what happens when the errors are not so simple, and Oracle’s [...]

In the introduction to this series of posts, I spoke briefly about data warehouse fault tolerance and the unique challenges resulting from high data volumes combined the batch load window required to create them. I then defined the goal: a layered approach allowing simple errors to be caught early before they turn in to serious [...]

With so much of the blog devoted to OBIEE, OWB and Essbase lately, I felt like it was time to do a few database-related postings. In the past, when I’ve posted database content to the blog, I usually gravitate toward ETL-related features: those that waffle between database administration and ETL development. But this time I’m [...]

Along with In-Memory Parallel Execution, another new feature that came along with release 11gR2 of the Oracle Database (or more correctly, version 2 of Exadata Storage Server) is Hybrid Columnar Compression. You’ll need Exadata to use this (though at one point is was part of the standard 11gR2 database beta, without an Exadata dependency), but [...]