Table of Contents

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  1. Preface
  2. Introduction
  3. Accessing Data Archive
  4. Working with Data Archive
  5. Scheduling Jobs
  6. Viewing the Dashboard
  7. Creating Data Archive Projects
  8. SAP Application Retirement
  9. Creating Retirement Archive Projects
  10. Retention Management
  11. External Attachments
  12. Data Archive Restore
  13. Data Discovery Portal
  14. Data Visualization
  15. Oracle E-Business Suite Retirement Reports
  16. JD Edwards Enterprise Retirement Reports
  17. Oracle PeopleSoft Applications Retirement Reports
  18. Smart Partitioning
  19. Smart Partitioning Data Classifications
  20. Smart Partitioning Segmentation Policies
  21. Smart Partitioning Access Policies
  22. Language Settings
  23. Data Vault Datatype Conversion
  24. Special Characters in Data Vault
  25. SAP Application Retirement Supported HR Clusters
  26. Glossary

Dimension Slices

Dimension Slices

Create dimension slices to specify how the data for each dimension is organized. When you run the segmentation policy, the ILM Engine creates a segment for each dimension slice in the data classification.
Dimension slices define the value of the dimensions you include in a data classification. Each dimension slice you create corresponds to a segment. You might create a dimension slice for each year or quarter of a time dimension. When you create the dimension slice you enter the value of the slice.
Every dimension slice has a corresponding sequence number. When you create a dimension slice, the ILM Engine populates the sequence number field. Sequence numbers indicate the order in which you created the segments. The slice with the highest sequence number should correspond to the most recent data. If the slice with the highest sequence number does not correspond to the segment with the most chronologically recent data, change the sequence number of the slice.

Dimension Slice Example

You need to save space on a production database. Most application users in your organization need access to only the current fiscal year of transactions in a general ledger application module. You decide to create segments for every fiscal year of transactions in the GL module and then compress the segments that contain data from previous years.
First you create a single-dimensional data classification with the time dimension. Then you add three dimension slices to the time dimension, one for each year of transactions. When you run the segmentation policy, the ILM Engine creates a segment for each dimension slice in the classification.

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