In the third part of this blog post series about star schema design, let’s have a look at a powerful, but for many people still unknown feature: Oracle Database In-Memory enables massive performance improvements for typical data warehouse queries.
Category Archives: Dimensional Modeling
New “Sales History” Sample Schema in Oracle 23c
The newest version of the Oracle sample schema “Sales History” (SH) finally contains current data again and is easier to install than the previous versions. If you work with star schemas, the SH schema is a must.
Star Schema Design in Oracle: Partitioning
Partitioning is one of the most powerful features for data warehouses in Oracle databases. In this blog post, I explain how it can be used for the physical design of star schemas. What is the recommended partitioning strategy for a star schema, and what are the advantages of partitioning?
Star Schema Design in Oracle: Fundamentals
What are the design rules for good performance in a star schema in an Oracle database? This blog post series introduces some recommendations for the physical database design. This first post is about constraints and indexes.
Star Schema Optimization in Autonomous Data Warehouse Cloud
Oracle Autonomous Data Warehouse Cloud does not allow to create indexes. Is this a problem for star schemas because no Star Transformation can be used? Or are the required bitmap indexes automatically created? A look under the hood of ADWC.
My Sessions at DOAG 2017
This year, I had the opportunity to present three sessions at the DOAG conference in Nuremberg – one on each conference day. Here a short summary of the sessions and links to the downloads.
Analytic Views: Powerful Oracle 12.2 Feature for Business Intelligence
Analytic Views are one of the main features for Business Intelligence introduced with Oracle 12c Release 2. They provide a lot of new possibilities for analytical queries on star schemas. This blog post gives an overview of the new functionality.
Attribute Dimensions and Hierarchies in Oracle 12.2
Oracle 12c Release 2 introduced Analytic Views, a new set of metadata objects that are very useful for Data Warehouses and Business Intelligence applications. In the first blog post about this new feature I will have a detailed look at two of the new object types: Attribute Dimensions and Hierarchies.
Derived Measures and Virtual Columns
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 Dimensions from a Data Vault Model
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.