2022.5 - DataClarity New Features and Enhancements

DataClarity 2022.5 brings the following features and enhancements:


Data Preparation




Use macro expressions in custom SQL

You can now use user-related macro expressions not only in calculations and filters but also when adding custom SQL queries in a dataset.

Additionally, you can use a new macro expression, ${user.attribute('attribute_name')}, to filter data against any attribute defined for a user in Access Manager.





Use custom SQL expressions in filter conditions

When adding filters in datasets, you can now specify filter conditions as custom SQL expressions, for example, “Country” LIKE ‘Canad%’ or Column = ${user.username}. The expressions are then added in SQL preview as any other conditions.




Rename a table when adding a new data source

Starting with this release, you can rename any new tables that you add to a dataset. In the Choose tables to import dialog, click More options, and then select Rename table.




Subsequently, the Rename > Data source option is renamed to Rename > Table in Step 3 of the dataset wizard.





Create extracts for datasets based on custom SQL data

You can now create extracts of the datasets that are based on custom SQL data.




Replace a connection used in a dataset

Now, you can switch data connections used for the dataset to another replacement connection of the same type, for example, SQL server to another SQL server connection. This may be especially useful when you create a dataset that is using a test database during the modeling phase but then want to configure the dataset to use production data connections.

You can switch a data connection by clicking More options for the needed data connection and selecting Replace connection in the following places:

  • Dataset wizard (Step 2)
  • Cataloging & Lineage
  • Dataset connections

In the Replace connection dialog that opens, you can view the list of your own and shared data connections.







Add calculations based on columns from different dataset tables

Now, when creating or editing a dataset, you can create calculations by using columns from different tables. To do so, in Step 3 of the dataset wizard, on the Data preview toolbar, click Calculations. In the Calculations dialog that opens, you can find all the dataset columns grouped by table.





Preview dataset tables as columns list

Starting with this release, you can view dataset tables as a column list including its type, source column name, and source table. To switch between the views, use the Column list view and Data view icons in the upper-right corner of the data table in Step 2 and in the upper-left corner in Step 3 of the dataset wizard.







Format numeric columns as strings

Now, you can format numeric type columns to be displayed as strings with no decimals or thousand separators. In other words, if you need to treat a numeric column containing such numbers as 10,000 as a dimension, you change its format to String. Numeric dimension columns are always displayed as unformatted strings by default.

In Storyboards, a new option is available in Column format for numeric type columns.




Open a storyboard from the subscription email

This release lets you include a link to the respective storyboard in the subscription email. This way, a subscriber can quickly review the latest updates by navigating to the live version of the storyboard instead of reviewing the attached screenshots. Access to the live storyboard depends on the subscriber's permissions for the storyboard and for the dataset that is used for the visualizations.

A new macro expression, ${storyboard.link}, is now available in the default subscription email to automatically generate a storyboard link.



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