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Please note
When describing the features, please ensure that the following questions are answered
Why are we doing this?
What problem are we solving?
For which target group are we doing this?
What is the value/added value we want to achieve?
yuuvis® RAD 9.14/9.16 LTS
We will present only highlights today. See all new features here:
Release Overview 9.x
Database Drivers are updated and PostgreSQL 16 is supported as well.
All Microservices are updated to Spring Boot 3.1.5 and CAMEL 4.1.0 (Martin, 3 Minutes)Business Value: Keep the application future-proof and secure
New: Some look & feel changes to the service manager interface
Client Request Signatures: The request signatures dialog is optimized (Martin: 3 Minutes)
Business Value: better productivity due to a better user experience
Client Create Objects: Users can change the newly selected object type for a bundle of files in the in-tray (Martin: 3 Minutes)
Business Value: better productivity while not repeating the file import
Client Form Tables: data import via CSV file (Martin, 6 Minutes)
Business Value: better productivity while avoiding manual typing
Client Chart Widgets: Introduction of partial values and histogram types year, month, week, and day for date properties (Martin, 3 Minutes)
Business Value: better productivity with statistics that show specific time axis
Client Dashboard: Performing a saved search from the dashbord needs fewer clicks (Martin, 1 Minute)
Business Value: better productivity
Client Settings: It is possible to store the locally saved client settings also to the server and reload them from here (Martin, 2 Minutes)
Business Value: better productivity while avoiding a daily setup
Management-Studio Operation: The new operation 'Synchronize retention' synchronizes the retention times set on storages (Martin: 3 Minutes)
yuuvis Momentum 2023 Winter LTS
Process and task management in architect (Bratislav: 5 minutes)
Business Value: administrators can manage running processes more efficiently
Kairos API (Wissal: 10 minutes)
Business Value: Use a machine learning pipeline to train a model and deploy it without prior AI knowledge.
core (Andreas: 10 minutes)
Batch-Update with Greedy-parameter
Prospect of service structures to be changed