Introducing DataConnect 12.2
We are pleased to announce the general availability of DataConnect 12.2. This release furthers our commitment to making it easy for our integration customers to connect, transform, and analyze data. With this release, customers will now have a faster path to the cloud using the Actian Data Platform to deploy existing integrations to cloud-based environments.
Highlights of the release include:
Bulk deployment of integrations to the Actian Data Platform
Previously, customers would need to deploy integrations to the Actian Data Platform individually. Customers can now take existing, or new .djars (projects/workflows) and deploy them to Integration Manager in bulk. This allows designers to expose integrations faster in cloud environments and applications.
EZScript Debugger Capability
The EZScript debugger makes designing and validating maps and processes that leverage EZScript much easier. Users can set breakpoints and test desired or expected behavior of EZScripts. Now all the debugging can be done in line with the DataConnect Studio editor. Engine execution pauses based on the breakpoints the user sets and values are displayed for any variable, macro, or object.
Integration Manager Client is now available in DataConnect Studio
This provides the ability to log into Integration Manager from the DataConnect Studio, browse existing configurations, and download the .djar and project files to the DataConnect studio if desired. Users have the option to explode the .djar files and import all the contents to a new project. This benefits clients that need to troubleshoot, edit, or extend integrations in Integration Manager.
New troubleshooting assistant
Provides detailed information about errors, suggestions on error resolution, as well as links to the Actian community posts and relevant help topics.
UX enhancements
For macros, Process Designer, message objects, and browsing. Macros can be created, edited, and accessed inline using DataConnect Studio and saved for reuse in the macro library.
Improved Data Quality metrics
Profile data to ensure data quality, including the ability to perform fuzzy matching across multiple fields in a dataset to identify duplicate records.
Direct upgrade
For customers on version 9 or later – full backward compatibility.
Click here to access the full release notes.
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Author: Chris Gilson