Table of Contents

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  1. Preface
  2. Introduction to Test Data Management
  3. Test Data Manager
  4. Projects
  5. Policies
  6. Data Discovery
  7. Creating a Data Subset
  8. Performing a Data Masking Operation
  9. Data Masking Techniques and Parameters
  10. Data Generation
  11. Data Generation Techniques and Parameters
  12. Working with Test Data Warehouse
  13. Analyzing Test Data with Data Coverage
  14. Plans and Workflows
  15. Monitor
  16. Reports
  17. ilmcmd
  18. tdwcmd
  19. tdwquery
  20. Appendix A: Data Type Reference
  21. Appendix B: Data Type Reference for Test Data Warehouse
  22. Appendix C: Data Type Reference for Hadoop
  23. Appendix D: Glossary

Amazon Redshift

Amazon Redshift

The following table describes the tasks that you can perform on data types in Amazon Redshift when the target is the test data warehouse:
Data Types
Test Data Warehouse
Comments
Bigint
Yes
Bool
Yes
Boolean
Yes
Char
Yes
Date
Yes
Decimal
Yes
Double Precision
Yes
Float
Yes
Float4
Yes
Float8
Yes
Integer
Yes
Int
Yes
Int2
Yes
Int4
Yes
Int8
Yes
Nchar
Yes
Numeric
Yes
Nvarchar
Yes
Real
Yes
Text
Yes
Timestamp
Yes
Varchar
Yes
You cannot perform tasks on the following Amazon Redshift data types:
  • Arrays
  • Bit
  • Bit Varying
  • Bytea
  • Composite types
  • Date/Time types
  • Interval
  • Time
  • Enumerated types
  • Geometric types
  • JSON
  • Network address types
  • Serial
  • Big serial
  • Small serial
  • Money
  • Object identifier types
  • Pseudo types
  • Range types
  • Text search types
  • Transaction ID snapshot
  • UUID
  • XML

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