The data processing function is a useful feature of SeaTable that allows you to perform operations on a column across multiple rows . By defining an operation, you can either perform various mathematical calculations or establish relationships between values in different tables. Data processing operations have a particularly great effect in large data sets where you can handle a high number of computational processes.
Sense behind data processing operations
SeaTable often thinks in rows. For example, a formula can exclusively relate the values in a row and also links between tables are only ever done from rows to rows.
Data processing, in contrast, is a function to perform operations in a column across multiple rows . Basically, a distinction is made between two different types of data processing operations:
- Mathematical calculations across all values in a column. Example: Access numbers to a web page.
- Relate values if they are identical in two tables. Example: assign payments received to an invoice.
Mathematical and relationship operations
The following mathematical operations can currently be performed using the data processing function:
The following relationship operations can currently be performed using the data processing function:
Requirements for the definition of operations
The two types of data processing operations each have different requirements that must be met in order to create a corresponding operation.
- Mathematical operations require the presence of two columns of numbers in your table.
- For the relation operations, you need very specific column types depending on the use case, e.g. an employee column and a text column when transferring user names.
Execution notes
Data processing operations can currently be performed manually or via automation. The development team is working to ensure that data processing operations can also be executed using buttons in the future.
Each time the data processing operation is executed, the results are written to the results column regardless. If you do not want to overwrite any data, you should create a new empty column for the results in advance.
Unlike formula columns that permanently monitor the columns involved, result columns do not update themselves. Changes to the values in the source column do not affect the values in the result column without automation or re-execution. Therefore, you can also manually overwrite the calculated or related values.
Protection against changes
To prevent misunderstandings, we recommend not to make manual changes to the columns involved and to lock them for editing after execution for safety (requires Plus or Enterprise subscription).
Be aware that the calculated or related values are a snapshot at the time of execution. If you do not execute the operation again, the results may be outdated if the values in the source column have changed in the meantime.
