For over a yr, Databricks AI/BI has been democratizing enterprise intelligence and analytics throughout your group with extremely visible and interactive low-code AI/BI Dashboards. Following a short point out in our most up-to-date AI/BI roundup weblog, we’re excited to showcase the flexibility to outline expressive, reusable customized calculations in AI/BI Dashboards. Customized calculations mean you can mannequin your knowledge in additional expressive methods on prime of supply datasets to create richer, extra interactive, and extra performant dashboards.
Customized calculations are outlined utilizing acquainted SQL syntax, so there’s no studying curve to make use of them. Crucially, customized calculations additionally mean you can outline aggregations and transformations on prime of your dashboard datasets with out modifying the unique dataset queries. They arrive in two kinds:
- Calculated measures are aggregated calculations that may be utilized dynamically throughout completely different groupings as wanted by completely different visualizations. Instance:
- Calculated dimensions are non-aggregated calculations which might be utilized row-wise. These are useful for formatting or reworking particular person row values. Instance:
Why use customized calculations?
Lowered dataset sprawl
Suppose you might have the next dataset:
You need to visualize revenue margin by area. With out customized calculations, you would want to create a brand new dataset with a margin column:
Whereas this strategy works, the brand new dataset is static and would possibly solely assist a single visualization. Filters utilized to the unique dataset don’t have an effect on widgets utilizing the brand new datasets with out extra handbook changes.
With customized calculations, you may categorical the revenue margin as an aggregation utilizing the method:
Although this measure is outlined on the unique, ungrouped dataset, it’s dynamic. When it’s utilized in a visualization, it robotically updates to replicate groupings and filters utilized to the dataset. On this instance, we are able to even use the identical customized calculation to calculate revenue margin per area in a single visualization, and revenue margin per product in one other visualization. With out customized calculations, this might require not less than two extra “bespoke” datasets outlined with the precise groupings.
To this point, utilization has indicated that dashboard authors want lower than half as many datasets to assist the identical variety of visualizations once they use customized calculations.
Extra unified interactive filtering
Interactivity is a key part of what makes AI/BI Dashboards highly effective. Nevertheless, interactive filtering by way of filter widgets and cross-filtering operates on a per-dataset foundation, which implies that ease of interactivity takes successful when visualizations are splintered throughout many datasets. In such circumstances, customers could must take further steps to filter all desired widgets.
Consolidating datasets as detailed above allows the identical filters to take impact throughout extra visualizations. This ends in a extra constant, intuitive expertise – widgets primarily based on the identical underlying knowledge are extra simply configured to react to the identical filters.
In fact, customized calculations are additionally supported in static filters outlined per-widget. You may learn extra about interactivity in AI/BI Dashboards right here.
Expressive formatting
Customized calculations embrace assist for over 40 completely different capabilities and expression syntaxes, overlaying primary arithmetic, aggregations, conditional case expressions, knowledge sort casting, and a slew of capabilities for string/date manipulation.
These capabilities enable for greater than what’s already provided within the visualization editors. For instance, you may:
- Assemble arbitrary strings utilizing the CONCAT and CONCAT_WS capabilities. Instance:
- Format dates utilizing the DATE_FORMAT operate. Instance:
- Create customized class strings utilizing CASE expressions. Instance:
Streamlined dataset authoring
The introduction of customized calculations enhances the dataset authoring expertise in some ways:
- Customized transformations will be siloed into well-labeled customized calculations, maintaining litter out of dataset textual content.
- A brand new dataset schema view particulars what fields can be found to reference in calculations, and their knowledge varieties.
- Instantaneous expression validation and knowledge sort inference computed client-side can be found for customized calculations.
- A semantically constant set of datasets to your dashboard is less complicated to attain when there’s much less dataset sprawl. Having fewer, extra coherent datasets minimizes confusion and additional “detective work” to relearn how your datasets are structured each time it’s essential to replace your datasets.
Efficiency inbuilt
Widgets utilizing customized calculations are topic to the identical efficiency optimizations as all different widgets in AI/BI dashboards. This consists of caching question outcomes and quick client-side computation for small datasets.
As well as, having fewer datasets that carry out much less complicated grouping operations ends in quicker dataset question execution, rushing up iteration time when authoring and decreasing load time when viewing.
Tips on how to create and use customized calculations
To create and use a customized calculation:
- On the related dataset, click on Customized Calculation.
- Within the panel that opens, fill out the Title and Expression fields, utilizing the dataset Schema View and built-in expression validation to information your expression authoring. Optionally, write a Remark describing what your calculation is doing. Click on Create.
- Now you can view your customized calculation within the dataset schema view and choose it simply as you choose some other subject within the visualization editor.
For full directions, see the customized calculations documentation. If you’re new to AI/BI dashboards, try this tutorial to get began.
Conclusion
Customized calculations carry a brand new degree of expressivity and suppleness to the AI/BI Dashboard authoring expertise and allow extra unified interactive experiences for dashboard customers. Try the documentation for much more particulars on methods to handle your customized calculations and for a full record of supported capabilities and expression syntaxes.
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We won’t wait to see what you construct with customized calculations, and worth your suggestions as we proceed to develop this function — tell us what assist for much more expressive calculations you’d wish to see!