Snowflake versus In-memory Features: Difference between revisions
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||Planned in PA 2023.2 | ||Planned in PA 2023.2 | ||
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|| | ||Calculated attributes to create reusable measures | ||
|style="text-align:center;"|X | |style="text-align:center;"|X | ||
||Planned in PA 2023.3 | ||Planned in PA 2023.3 | ||
|- | |- | ||
|| | ||Conformance analysis using BPMN design models | ||
|style="text-align:center;"|X | |style="text-align:center;"|X | ||
||Planned in PA 2023.3 | ||Planned in PA 2023.3 | ||
Revision as of 11:42, 1 March 2023
This page describes differences in available features between in-memory and Snowflake dashboards.
| Feature | In-memory | Snowflake |
|---|---|---|
| Event filtering based on event attributes and expressions (by any criteria) | Only by event types | X |
| Filter rules can be defined for measures and dimensions | X | |
| Dynamic event type mapping (allows to set event type for each chart/flowchart) | X | |
| Business calendar for duration calculation | X | Planned in PA 2023.2 |
| Define measures as variables to build combined measures | X | Planned in PA 2023.2 |
| Statistical aggregations (median, standard deviation, variance, percentile) | X | Planned in PA 2023.2 |
| Calculated attributes to create reusable measures | X | Planned in PA 2023.3 |
| Conformance analysis using BPMN design models | X | Planned in PA 2023.3 |
| Case level permissions for granular access control | X | Planned in PA 2023.4 |
| Notifications and alerts to initiate corrective actions | X | Planned in PA 2023.4 |
| Root causes analysis for flowchart and some advanced chart presets | X | Planned in PA 2023.4 |
| Loops and advanced programming logic in custom expressions | X | |
| Define custom aggregations using expressions | X | |
| Machine learning functionality (e.g., prediction, clustering) | X |