Table of Contents

Search

  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. Salesforce Archiving
  9. SAP Application Retirement
  10. Creating Retirement Archive Projects
  11. Integrated Validation for Archive and Retirement Projects
  12. Retention Management
  13. External Attachments
  14. Data Archive Restore
  15. Data Discovery Portal
  16. Data Visualization
  17. Oracle E-Business Suite Retirement Reports
  18. JD Edwards Enterprise Retirement Reports
  19. Oracle PeopleSoft Applications Retirement Reports
  20. Smart Partitioning
  21. Smart Partitioning Data Classifications
  22. Smart Partitioning Segmentation Policies
  23. Smart Partitioning Access Policies
  24. Language Settings
  25. Appendix A: Data Vault Datatype Conversion
  26. Appendix B: Special Characters in Data Vault
  27. Appendix C: SAP Application Retirement Supported HR Clusters
  28. Appendix D: Glossary

Multidimensional Data Classification

Multidimensional Data Classification

A multidimensional data classification uses more than one dimension to divide the application data into segments.
You can include more than one dimension in a data classification, so that Data Archive uses all the dimensions to create the segments. When you apply multidimensional data classifications, the ILM Engine creates segments for each combination of values.
For example, you want to create segments for a segmentation group by both a date range and sales office region. The application has three years of data that you want to create segments for. You choose the time dimension to create segments by year. You also create a custom dimension called region. You configure the region dimension to create segments based on whether each sales office is in the Eastern or Western sales territory.
When you run the segmentation policy, the ILM Engine creates seven segments, one for each year of data from the Western region, one for each year of data from the Eastern region, and a default segment. Each non-default segment contains the combination of one year of data from either the East or West sales offices. All remaining data is placed in the default segment. The remaining data includes data that does not meet the requirements for a segment, such as transactions that are still active, plus all new transactions.

0 COMMENTS

We’d like to hear from you!