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- Limit fields for Guided NLQ
Fewer fields keep Guided NLQ running quickly and aid users who may be bogged down by too many field choices. - Understand filter value caching
Guided NLQ is already fast, and the Load Filter Values gives you extra flexibility during configuration - Provide meaningful field names
Descriptive field names help first-time users get started. - Add plurals
Adding a plural to a field name ensures a more natural question flow for Guided NLQ users. - Prepare intuitive calculated fields
Consider creating calculated fields to help your users formulate simpler questions. - Prepare non-continuous date fields
Use date functions to create additional ways to analyze your data. - Create popular focus areas
Focus areas enable quick and simple refinement of complex data, saving users from writing long, complicated questions. - Match user access to skill level
Very complex views should only be given to users with a high degree of data skill and familiarity with the data sets — including NLQ access - Organise a date hierarchy
Data aggregation results may differ if date hierarchies aren’t correctly set up.
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Date hierarchies are regular drill down hierarchies, except they drill from coarse-grained to fine-grained temporal fields, in the correct order — Year— Year, Month, Day, for example. You can apply date functions to manufacture more coarse grained fields, such as the "month start date" date function to the Start Date field (which has daily day granularity), which would produce a new version of the Start Date field with monthly granularity.
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