References → Change Type Recipe
This recipe is designated to transform the data type of an existing column to a new data type. Generally, best practices would dictate that the data type is correctly configured in the schema, but there are scenarios where data types need to be updated during transformation.
Configuration
Configuration | Description |
---|---|
Recipe Name | A freeform name of how a user would like to name a recipe |
Input | Select a previously constructed recipe to process |
Change Column Type | Select a column to be transformed into a new type. Next, select the type to transform it into. |
Data Type Options
Type | Description |
---|---|
String | Ideal for storing short to medium variable-length character data. |
Text | Ideal for storing long variable-length character data. If you choose to output this type to an MV, downstream reporting will not allow this as a grouping dimension. |
Integer | A 32-bit integer ranging from -2,147,483,648 to 2,147,483,647 |
Long | A 64-bit integer ranging from -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807 |
Double | A floating-point number handles decimal points for optimal precision. |
Date | Convert to a date represented as YYYY-MM-DD. Note that the string value must be in this format before conversion. |
Timestamp | Convert to a datetime represented as YYYY-MM-DD HH:MM:SS. Note that the string value must be in this format before conversion. |
Boolean | Convert a flag field (0,1) to Boolean true/false data type. |
Incorta dataflows will always try to enforce datatypes in conversion. If the resulting data turns to NULL
, the value is incompatible with the target data type.
For example:
- Converting the word “Incorta” to an Integer will result in a
NULL
value. - Converting the string “Sept-13,2024” to Date will result in a
NULL
value.
Note
If the schema in the dataflow has a changed datatype, go to ‘...’ and select the Refresh Schemas option.