Having rich date dimensions in a data warehouse often enables sophisticated business relevant analytical queries. This post shows a way to generate a detailed date dimension table that includes fixed date and variable date holidays, working days, special events and week of year information using the Kettle ETL tool, also known as Pentaho PDI. . . . → Read More: Building a detailed Date Dimension with Pentaho Kettle
Date dimensions are among the most important dimensions of many Mondrian cubes. The usefulness of a cube often depends on the way the date dimension has been modeled. This post shows how to create a basic date dimension and how it can be augmented with properties to suit specific analysis needs. If at some point you . . . → Read More: A Simple Date Dimension for Mondrian Cubes
The previous post explains how to create a star schema for a Mondrian cube. The dimensions in the example data were very simple. Each dimension had only a single field whose value ended up being a member in the cube. In this post I would like to build a cube that has dimensions with multiple levels. . . . → Read More: A Basic Mondrian Cube: Using Multi-Level Dimensions
The previous post explained how to create a simple Mondrian cube. It is meant to provide the most basic information on how Mondrian cubes are created and stored. The previous solution uses only one DB table to store the entire cube. It uses only degenerate dimensions, to use Mondrian parlance.
This article builds on the basics already . . . → Read More: A Basic Mondrian Cube: Introducing the Star Schema