Most of what you see in Views can be produced by the Data Assistant using simple commands. At present, the Data Assistant does not support the following:
Queries on Lists and Tables
If you have key information stored in Lists, consider creating Metrics from that data so the AI can answer queries on it. For example:
you have a Dimension List that contains prospects over time
your Members want to know total prospects at year-end
you create a dedicated Metric âProspects countâ that counts up the number of prospects per Month from your List, and set it as AI-accessible
the Data Assistant fetches your Metric even though the source data is in a List
Queries on Snapshots
For example:
Scenarios that come from Snapshot Scenarios
Custom aggregators (including average)
While you canât currently ask the Data Assistant to show you averages from your data, you can create a Metric to address this, and make it AI-readable:
your Sales teamâs monthly forecasts are in the Metric âMonthly Revenue Forecastâ
your Members want a month average
you create a dedicated Metric âAvg Monthly Rev Forecastâ that calculates the average using Pigmentâs
averagefunction, and set it as AI-accessiblethe Data Assistant fetches your Metric when Members query âaverage monthly rev forecastâ
Sorting by Dimension property
Pivoting Dimensionsâ Rows and Columns
Combined charts
Complex calculations
For example:
Ratio between specific item and its total: âHeadcount in Spain / total headcountâ
Sorting by calculations: âSort products by YoY revenue growthâ
Cumulative calculations: âYear to Date Budget Costsâ
Application variables
For example:
âFilter on current Forecastâ
Formatting
For example:
âShow revenue as M$â
Make sure that all AI-readable Metrics have default formatting set up.
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