Catalog
Result Modification
Result Modification – Instructor Led Training
This three-hour course is for power users who want to use commands
to manipulate output and normalize data. Topics will focus on specific
commands for manipulating fields and field values, modifying result
sets, and managing missing data. Additionally, students will learn how
to use specific eval command functions to normalize fields and field
values across multiple data sources.
Result Modification (eLearning with labs) – Course
This three-hour course is for power users who want to use commands to manipulate output and normalize data. Topics will focus on specific commands for manipulating fields and field values and modifying result sets. Additionally, students will learn how to use specific eval command functions to normalize fields and field values across multiple data sources.
Result Modification (eLearning) – Course
This three-hour course is for power users who want to use commands to manipulate output and normalize data. Topics will focus on specific commands for manipulating fields and field values and modifying result sets. Additionally, students will learn how to use specific eval command functions to normalize fields and field values across multiple data sources.
Result Modification (eLearning) - Japanese Captions – Course
This three-hour course is for power users who want to use commands to manipulate output and normalize data. Topics will focus on specific commands for manipulating fields and field values and modifying result sets. Additionally, students will learn how to use specific eval command functions to normalize fields and field values across multiple data sources.
Result Modification (eLearning with labs) - Japanese Captions – Course
This three-hour course is for power users who want to use commands to manipulate output and normalize data. Topics will focus on specific commands for manipulating fields and field values and modifying result sets. Additionally, students will learn how to use specific eval command functions to normalize fields and field values across multiple data sources.
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