Earlier Releases of Dataprep by Trifacta

Intelligent caching:

Due to technical issues, the intelligent caching of recipe steps feature for performance improvements has been disabled.

When the technical issues are addressed, this feature will be enabled.

Lock/unlock column data type:

You can now lock or unlock a column's data type. When the data type is locked, the Trifacta Application no longer attempts to infer the column's data type when subsequent recipe steps are applied.

For more information, see Change Column Data Type.

Connectivity:

Early Preview (read-only) connections available with this release:

Connectivity:

Publish Array data type as arrays to BigQuery:

You can now publish Dataprep by Trifacta Array data type as BigQuery arrays.

Parameterize data in hidden folders:

Optionally, you can scan hidden folders for wildcard- or pattern-based matches when building your parameterized imported datasets.

For more information on including hidden files, see Dataprep Project Settings Page.

For more information on creating datasets with parameters from files, see Parameterize Files for Import.

Simplified permissions for publishing to BigQuery:

By default, Dataprep by Trifacta requires that the bigquery.datasets.create permission is enabled for each user of the product to run Dataflow jobs on BigQuery data sources. In some environments, this permission cannot be provided to users, and these Dataflow jobs fail.

As a workaround, you can provide to Dataprep by Trifacta a pre-existing BigQuery dataset, in which intermediate query results can be stored. When this dataset is provided to the Trifacta Application, temporary tables are created within it as part of Dataflow job execution, and the bigquery.datasets.create permission is not required.

For more information on configuring the BigQuery temp dataset for the Trifacta Application, see Dataprep Project Settings Page.

Documentation:

Published documented solution for integrating Dataprep by Trifacta with your Virtual Private Cloud Service Controls (VPC SC). For more information on this integration, see Configure VPC-SC Perimeter.

Set column data type transformation locks the column's type by default:

Starting in this release, the column data type is locked by default when you change the column data type.

If required, you can unlock the column's data type. For more information, see Change Column Data Type.

Connectivity:

Generate an initial sample:

When generating an initial sample from a set of files in a directory, the maximum number of files that can be read is now limited to 50.

As needed, an administrator can change this maximum limit.

Performance:

The intelligent caching of recipe steps feature for performance improvements has been made available again. The issues that required removing it from the platform have been addressed.

This feature can be enabled by an administrator.

For more information, see Dataprep Project Settings Page.

Email notifications:

In a future release, the setting for email notifications based on job success will default to Default (Any Jobs) at the project or workspace level and at the flow level. This change means that the user who executes a job and others who have access to the flow receive, by default, an email notification whenever a job executes for flows where email notification settings have never been modified. As part of this change, each email will contain a richer set of information about the job that was executed.

If needed, this new default setting can be modified:

None.

Encryption:

JavaScript User Defined Functions:

Connectivity:

Connectivity:

Early Preview (read-only) connections available with this release:

Job execution:

The Trifacta Application can check for changes to your dataset's schemas before jobs are executed and optionally halt job execution to prevent data corruption.

Dataset configuration:

For an imported dataset, you can configure settings through a new interface, including column names and column data types to use in the Trifacta Application.

Sample Job IDs:

When a sample is collected, a job ID is generated and displayed in the Trifacta Application. These job IDs enable you to identify the sample jobs.

Import:

For long-loading Parquet datasets, you can monitor the ingest process as you continue your work.

For more information, see Flow View Page.

Publishing:

Beginning in this release, you can publish Dataprep by Trifacta Array type columns to BigQuery as BigQuery arrays for Alteryx primitive data types. Arrays containing non-primitive data types continue to be published as String values.

Performance:

A recent release introduced improved performance through intelligent caching of recipe steps.

None.

None.

JavaScript User Defined Functions:

Create user-defined functions (UDFs) in JavaScript and upload them to your project for use in your recipe steps. JavaScript UDFs enable users to create customized and consistent functions to meet their specific requirements.

For more information, see JavaScript UDFs.

When enabled, JavaScript UDFs are defined through the Library page. For more information, see User Defined Functions Page.

Connectivity:

Build connections to accessible REST API endpoints.

For more information, see REST API Connections.

Connectivity:

Early Preview (read-only) connections available with this release:

Dataset Schema Refresh:

You can now refresh your imported datasets with the current schema information from the source file or table. Schema refresh enables you to capture any changes to the columns in your dataset.

None.

None.

None.

None.

None.

None.

None.

BigQuery Running Environment:

Beginning in this release, sampling jobs can be executed in BigQuery.

Connectivity:

Early Preview (read-only) connections available with this release:

Session Management:

You can view the current and recent sessions of the Trifacta Application. You can review the devices that are authorized and revoke any unfamiliar devices.

Performance:

None.

None.