DataClarity 2022.4 brings the following features and enhancements:
- Share underlying sources when sharing a storyboard
- Include custom palettes in the exported storyboards
When creating a dataset based on a relational database, you can now select tables and columns by using SQL queries. With this new capability, advanced users can speed up a dataset creation process by inserting existing code instead of manually selecting tables and adding calculations or filters. Moreover, SQL queries allow for greater flexibility in custom data selection.
To switch to the SQL query mode, click Custom SQL when creating a new data connection or adding a new source to a dataset. In the new SQL query pane, you can type your SQL statement, and then instantly verify the results by clicking Preview.
For your convenience, the code editor highlights the SQL keywords. You can also resize sections for the code editor and preview by dragging the line separating the sections of the pane.
Previously, new columns that you added to a dataset in Step 2 and Step 3 of the dataset wizard could be renamed only individually. Now, when adding a new column to an existing data source table, you can also rename multiple columns at once in the Add column dialog.
Previously, to share a storyboard for further editing, you needed to manually find and share each of the underlying datasets, AI connections, and custom palettes. Now, you can choose to share all the underlying sources that are used to build a storyboard at once. To do so, go to a storyboard that you want to share, select Share, and then select the Share underlying resources option. To share a storyboard for viewing purposes only, leave the option deselected.
If a storyboard uses a custom palette, you no longer need to share or recreate them in the imported storyboards. Starting from this release, all the custom palettes are included in the exported archive file.