Added ability to process database tables by wildcard name
Previously, to extract and load data from/to multiple database tables you would have to create separate pairs of source-to-destination transformations.
In this update, we introduced an ability to process database objects (tables and views) by wildcard names.
- How to move tables matching a wildcard name from one schema or database to another
- Loading multiple table into Snowflake by wildcard name
- Loading multiple table into Amazon Redshift by wildcard name
Added CLOB format which can be used to easily transform the text messages
The most powerful transformation is in Etlworks source-to-destination. In almost all cases it hides the complexity of working with specific data formats and allows ETL developers to use high-level instruments, such as mapping editor.
There are cases, however, when you just want to make a few changes in the source text document and save it to the same or different location.