Key Focus Areas For Update
Table Explorer in Tabs
Viewing table and view data in Table Explorer previously presented items in a modal window. Table Explorer is now opened as a separate tab so multiple tables can be viewed and compared, as well as kept open while other actions are taken.
Improved Navigation Speed
We continue to search for more ways to help improve productivity in PlaidCloud. One of the improvements in this release is faster navigation speed and viewing of information. In the past, when viewing workflows in projects with many steps or significant numbers of tables (e.g. > 5,000), the presentation of information could take several seconds. This has been addressed and should now render quickly.
Improved Data Mapper Column Moving
The data mappers now allow for groups of rows to be moved. In addition, the move operation is now available in the menu rather than requiring a right-click operation. This should allow moving a column or groups of columns much more quickly.
Improvements to Assignments and Allocations
Subtle improvements and speed-ups for assignments and their application in allocations. These are minor improvements that should help with use.
Improved Error Presentation
We all hope we don’t make mistakes but when we do, getting relevant information quickly is critical for fixing the problem. In this release, several improvements to error messaging will help direct you to the specific error rather than having to sort through large stack traces, which can be time consuming and confusing in some cases.
Better Handling of Project Names on Export
In the past, odd behavior would occur when exporting a project with a “/” in the name. The slash (“/”) was interpreted as a path element. This is now replaced with an underscore (“_”) to the project export appears in the expected location.
Melt Value Column Data Type Setting
Previously, the data type of a Melt operation was determined by choosing the data type of the columns if they were all the same or defaulting back to Text if there were any differences. This often caused the need to add an Extract step after a Melt to set the data type. The Melt transform now allows setting a desired data type directly in the step.