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

Single-dimensional Data Classification

Single-dimensional Data Classification

A single-dimensional data classification uses one dimension to divide the application data into segments.
Use a single-dimensional data classification when you want to create segments for application data in one way, such as by year or quarter. Single-dimensional data classifications often use the time dimension.
For example, you manage three years of application data that you want to divide into segments by quarter. You create a time dimension and select range as the dimension type and date as the datatype. When you run the segmentation policy the ILM Engine creates 13 segments, one for each quarter and one default segment. The data in the default segment includes all of the data that does not meet the requirements for a segment, such as transactions that are still active. The default segment also includes new transactional data.

0 COMMENTS

We’d like to hear from you!