Table of Contents

Search

  1. Preface
  2. Introduction
  3. Working with Enterprise Data Manager
  4. Enterprise Data Manager
  5. ILM Repository Constraints
  6. Partition Exchange Purging
  7. APIs
  8. Smart Partitioning
  9. Salesforce Accelerator
  10. SAP Application Retirement Entities
  11. Import Formats for Constraints
  12. Glossary

Enterprise Data Manager Guide

Enterprise Data Manager Guide

Dimensions

Dimensions

A dimension determines the method by which the segmentation process creates segments, such as by time or business unit. Dimensions add a business definition to data, so that you can manage it easily and access it quickly. You create dimensions during smart partitioning implementation.
The Data Archive metadata includes a dimension called time. You can use the time dimension to classify the data in a segment by date or time. You can also create custom dimensions based on business needs, such as business unit, product line, or region.
When you implement smart partitioning, you choose to use single-dimensional or multidimensional data classifications. A single-dimensional data classification uses one dimension to create segments. A multidimensional data classification uses more than one dimension to create segments.
When you create a dimension, you must configure the type and datatype. The type can be list or range, and the datatype can be date, number, or string. If you want to reuse a dimension, you can associate it with any segmentation group.
Before you begin the segmentation process, you create dimension slices that specify how the data is organized on the dimension. The first time you create segments for a segmentation group, the ILM Engine leverages native database partitioning methods to create segments for each dimension slice in the data classification.

Dimension Example

A group of application users need access to only the current fiscal year of transactions in an accounts receivable application module. To save space on your production database you decide to create segments for every fiscal year of transactions in the AR module and then compress the segments that contain data from previous years. You choose the time dimension with a type of range and a datatype of date. In the Data Archive user interface you add dimension slices for the time dimension you created. When you schedule the segmentation process, the ILM Engine creates a segment for each dimension slice.
The following table shows dimension slices for the time dimension that you configured:
Dimension Slice Name
Dimension Slice Value
FY2012
Jan 1, 2012 – Dec 31, 2012
FY2011
Jan 1, 2011 – Dec 31, 2011
FY2010
Jan 1, 2010 – Dec 31, 2010

0 COMMENTS

We’d like to hear from you!