This release focused on performance improvements.

This release improves query management in Zap Live with easier worksheet organization, renaming, and reordering, while also removing hierarchy limits for custom queries and allowing multiple views of the same Data Hub report. In Zap Analytics, you can now quickly flip the sign of any member in an Analysis Table to better represent cash flow.

Zap Live now includes generally available custom queries, a new resource explorer for easier report loading, and table formatting that follows data rather than worksheet position. Additionally, modeling enhancements include on-demand refresh capabilities for Analysis reports and improved Dynamics 365 Business Central Cloud connector with dynamically generated extensions.

Zap Live now supports global filters that apply across all workbook queries and improved axis summaries from Data Hub reports. Modeling enhancements include configurable fiscal year start dates for partitioning, and new warehouse maintenance options for storage optimization.

Zap Live now allows users to open named sets, calculated members, and pipelines directly from the dimension tree for easier editing. The release also includes standard performance improvements and bug fixes.

This release introduces the ability to raise support tickets directly from Data Hub, a preview of custom query design in Zap Live, and several modeling enhancements.

This release was focused on bug fixes and performance improvements, especially for Zap Live.

This release includes Zap Live, a new Excel add-in that connects to Data Hub analytics from within Excel, as well as modeling improvements such as clickable pipeline links in the process tree and enhanced partitioning resilience for loading large tables.

This release includes the full release of Zappy (an AI assistant) and weekly AMA sessions, alongside technical improvements to the Excel Online and SAP B1 connectors.

This release introduces a new delta pipeline processing type for significantly faster add and update processing of large datasets, along with general performance enhancements and bug fixes.