Building on v3.0.1, this version further improves business planning, data modeling and indicator management. It adds version management for business entities and multiple model types, and optimizes data standard association, data integration task validation and FTP file access — continuing to improve platform completeness and stability.
Here’s what’s new:
- Modeling overview and category tree statistics
The modeling overview now includes statistics for data domains, subject areas, conceptual models, logical models, indicator models and published models, and supports viewing model layering distribution and model status distribution.
A new “latest activity” section covers additions, modifications and deletions of logical models and indicator models, as well as logical model publishing.
The category tree now improves object counts for subject areas and conceptual models; source-aligned, dimension, fact, summary and application logical tables;
and atomic indicators, business constraints and derived indicators. Users can drill down from the data domain list to the business planning page, and from the subject area list to the business entity page, with corresponding filters automatically applied.
- Business entity relationship management and historical versions
qData v3.0.1 supports maintaining relationships between business entities, including inheritance, association, flow, predecessor/successor and containment. Relationship validation is improved during business entity creation and editing, and conceptual model relationship data is maintained based on entity relationships.
The business entity list now displays inheritance and containment relationships, supports expand/collapse and one-click expand/collapse, and allows users to view the conceptual model diagram of entity relationships.
A new business entity version management capability supports viewing historical versions and comparing differences between versions.
- Conceptual model relationship graph
A new conceptual model relationship graph is added, with filtering, viewing, editing and linked operations. It supports displaying conceptual model categories by data domain, subject area, business object classification and business object layering.
The left side supports filtering by data domain, subject area and business entity. Users can click relationship-type legends to highlight corresponding relationships, click node legends to highlight nodes, and select a node to highlight its entire related node relationship. Entity node and relationship details can also be viewed.
The graph supports quick editing of business entities, and creating logical tables, sub-objects and associated entities directly from the graph. Legends for node types and relationship types can be expanded or collapsed, and clicking a legend highlights corresponding nodes or relationships on the canvas. The relationship graph can also be viewed in the business entity tab of data domain details.
- Logical model design optimization
For source-aligned logical tables, the update adds source physical table structure detection and synchronization, supporting manual detection of structural changes and synchronization to the source-aligned logical table. Model history versions can be viewed and compared.
For dimension logical tables, the platform supports automatic generation of foreign key fields and associated dimensions based on entity relationships. Default fields and field attributes can be modified. Multiple associated dimensions can be configured, with automatic matching and display of associated dimension information based on associated business entities.
If the selected business entity does not yet have a corresponding logical table, users can quickly create one during associated dimension selection. Dimension logical tables also support importing fields from existing logical tables and generating table structures through SQL parsing.
For version maintenance, application table version maintenance capabilities are also listed, including viewing model history versions and comparing different historical versions.
For fact logical tables, business event tables support automatic generation of primary keys, associated entity IDs and event time fields. Business process tables support automatic generation of primary keys, associated event time, process start time and process end time fields. Default fields can be modified, field attributes maintained and fields manually added, and multiple associated dimensions configured. Business event tables support automatic matching and display of associated dimension information based on associated business entities, with quick creation of logical tables if needed. Fact logical tables support importing fields from existing logical tables and generating table structures through SQL parsing. Version maintenance provides application table history version viewing and comparison.
For application logical tables, the update supports importing fields from derived indicators, data elements and code tables, and generating table structures through SQL parsing. Users can view application table model history versions and compare different historical versions.
For summary logical tables, when creating or maintaining derived indicators, the platform automatically matches summary logical tables based on the selected statistical granularity and establishes ownership between derived indicators and summary logical tables. Users can view associated logical table information in the upstream dependencies of derived indicators. Summary logical tables also support viewing model history versions and comparing different historical versions.
- Indicator management and new derived indicator module
Atomic indicators now support viewing bound derived indicators in their details, and add version management with historical version viewing and comparison.
Business constraints now support viewing associated derived indicators, and improve version management and historical version comparison. For business constraints with downstream dependencies, a dependency protection mechanism restricts destructive editing, deletion and disabling operations that may affect downstream use.
indicator management module supports viewing and managing derived indicators. Users can filter by derived indicator name, associated summary logical table and status, and add, view details, modify, delete and manage status. The list displays derived indicator information, ownership information, atomic indicators, business constraints and statistical periods. Details include basic information such as name and ownership. A new upstream dependencies tab shows associated logical table information, including logical table name, type and ownership.
Derived indicator version management supports viewing historical versions, version generation time, change type and operator, and comparing different versions with field-level differences.
- Data standard association, data integration and FTP access
For data standards, when asset fields are bound to data elements or code tables, the details of the corresponding data element or code table display information about the currently associated assets.
For data integration tasks, pre-execution configuration and parameter validation are enhanced, with relevant logs output. Validation is improved for cases such as insufficient database field length that may cause task failure. For insufficient task memory and resources, guardrail handling and resource configuration suggestions are further improved.
The FTP input component is optimized for multi-file access when an FTP directory contains multiple data files, TXT file parsing when TXT files are used as input with field separators, and cleanup of processed files after FTP file access.
In summary
qData Data Middle Platform v3.0.1 continues to improve product capabilities around two main lines: data modeling and indicator management.
At the business planning level, it adds business entity relationship maintenance, historical version management and conceptual model relationship graph interaction.
At the logical model level, it improves source table structure detection and synchronization, dimension and fact logical table field design, application logical table field import, summary logical table and derived indicator association, and historical version viewing and comparison for multiple model types.
At the indicator management level, it adds a derived indicator management module and improves association viewing and version maintenance for atomic indicators and business constraints.
The platform also improves associated asset information for data elements and code tables, and optimizes pre-execution validation, resource configuration suggestions and the FTP input component for data integration tasks.
qData Professional Edition will continue to advance product iteration around actual usage needs and gradually improve data middle platform capabilities.
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