Ataccama 14.4.0 Release Notes

ONE components are now shipped with and support Java 17 where applicable. All servers running ONE components need to be upgraded to Java 17 when upgrading self-managed, on-premise deployments to version 14.4.0. For more information, see ONE Gen2 Upgrade Guide, MDM 14.4.0 Upgrade Notes, RDM 14.4.0 Upgrade Notes.

It is now possible to apply DQ evaluation rules directly to attributes in the catalog item rather than just to terms, meaning that you can run the same evaluation in the catalog as in monitoring projects.

This is important in cases where results have been exported from monitoring projects, remediated in ONE Data, and now, you want to re-evaluate them from the catalog. For more information, see Add DQ Rules to Attributes.

We introduced a new type of detection rules: rules based on metadata. Similarly to the existing data-based detection rules, they are used for term detection during profiling.

Metadata-based rules help assign terms based on the attribute name and can be used together with data-based rules, which increases the accuracy of term detection during profiling. For more information, see Detection and DQ Evaluation Rules.

The data reconciliation feature provides high-level checks of data consistency across multiple sources. This allows you to verify, for example, that the target data is the same as the source data when migrating from one database to another, so you know that the original data was transferred without any data leakages or malformations. For more information, see Data Reconciliation.

We renamed the approval workflow to Review request workflow. In addition, all workflows are now managed from a single place: the Workflows tab.

The Review request workflow offers additional automation for requesting reviews of changes made to data assets and publishing these changes in ONE. If you have editing access level on an entity and are making changes to an asset, you can use it to send your changes for review. After this, the person responsible for the task can reject or approve and publish your changes. For more information, see Publish Changes and Workflows.

By default, Databricks uses a perpetually running generic cluster (with autosleep) that is configured once and can run multiple Spark jobs simultaneously. You now have the option to use a dedicated Databricks Job cluster.

With this type of cluster, the Databricks job scheduler creates a new job cluster whenever a job needs to be run and terminates the cluster after the job is completed. Depending on your use case, this can bring the following advantages:

For more information, see Databricks Configuration, Databricks job cluster configuration section.

You can now change the language of ONE to your preferred option. For more information and other basic features, see Application-wide Features.

Currently, the following languages are available:

Audit log entries related to sharing access and stewardship assignment (Manage access and Transfer stewardship) now include information about the access levels, groups, and users involved in the operations.

You can find this information in the new Additional Information card after selecting a relevant log entry. For some properties, you can drilldown for further details.

Add any DQ rule directly to catalog item attributes from the table or the attribute details sidebar. This allows you to apply specific DQ rules on particular attributes without modifying the default rule configuration for any of the assigned terms.

To do this, expand the list of DQ rules on the attribute and select Add Rule, then choose all rules that you want applied. Alternatively, right-click the attribute name and select Open details. The Add Rule option is available under DQ Rules.

If you change your mind or no longer want to use a manually assigned rule, select the X icon next to it to remove it and publish the changes.

You can also pause applied rules either directly from the table or from the attribute details sidebar by clicking the pause icon. After you publish the change and rerun DQ evaluation, the rule is no longer used in evaluation until you reactivate it.

When creating a table from a catalog item, you can now import the entire dataset together with DQ results to ONE Data, which lets you use DQ filters in ONE Data right after import. Previously, importing DQ results was available only for invalid records.

To do this, select the catalog item you want to export to ONE Data and then choose the following options: Full (data with DQ results) and All records. For more details, see Create a Table.

Importing datasets into ONE Data is now significantly faster: if your table contains 20 attributes, the data is loaded 70 times quicker compared to the previous version, provided that the import does not include DQ results. The actual loading speed depends on the number of attributes and records in the table.

We introduced a new powerful tool for efficient data visualization and analysis: Pivot tables. This brings you the following advantages:

We removed Data Grid widget as pivot tables offer more customization. If your previous stories or dashboards used a Data Grid widget, you can still see it in your report, but you can no longer interact with it, update it, or create a new one.

Data Stories now offers KPIs and Gauge charts, allowing you to present and customize key metrics with clarity. Create visually engaging KPIs and Gauge charts to track performance trends, compare metrics, and visualize progress towards targets.

You can also integrate KPIs and Gauge charts into stories for enhanced storytelling and impactful data communication.

MDM Web App can be now localized. Attribute labels, validation messages, and reference data can be translated to one of the supported languages: English, French, German, Italian, Czech, or Russian.

After you switch the language in the application, the translation to the currently active language is used automatically if available. The functionality needs to be manually configured first.

To learn more about localizing validation messages, see Configuring Validations, section Localize validation messages. For more information about reference data localization, see Working with Reference Data, section Reference data localization.

You can now use value suggestions in MDM Web App when you edit record values.

Autocorrects are suggestions of correct values based on simple underlying rules (for example, capitalizing the first name) and are applied to one field.

Enrichments provide one or more value suggestions based on more complex logic and allow to automatically populate several fields. For example, after filling in the street, the enrichment can help you add the whole address. Confidence is provided as part of enrichment suggestions so that you can select the set of values based on the score.

To use autocorrects and enrichments, you need to configure them first (see Configuring Enrichments and Autocorrects).

To determine your upgrade path, see MDM 14.4.0 Upgrade Notes.

We made working with records in RDM easier and more intuitive. The Create record and Edit record dialogs are now sleeker and simpler, allowing you to view more data at once and validate it on the fly.

To determine your upgrade path, see RDM 14.4.0 Upgrade Notes.