The Field Extractor Utility (FX) is a tool that helps you extract fields from your events using a graphical
interface or by manually editing the regular expression2. The FX has a button that displays events that do not
contain extracted fields, which is the Non-Matches button2. The Non-Matches button shows you the events
that do not match the regular expression that you have defined for your field extraction2. This way, you can
check if your field extraction is accurate and complete2. Therefore, option B is correct, while options A, C and
D are incorrect because they are not buttons that display events that do not contain extracted fields.

Explanation
The relationship between data models and pivots is that data models provide the datasets for pivots. Data models are collections of datasets that represent your data in a structured and hierarchical way. Data models define how your data is organized into objects and fields. Pivots are user interfaces that allow you to create data visualizations that present different aspects of a data model. Pivots let you select options from menus and forms to create charts, tables, maps, etc., without writing any SPL code. Pivots use datasets from data models as their source of data. Pivots and data models are not the same thing, as pivots are tools for visualizing data models. Pivots do not provide datasets for data models, but rather use them as inputs.
Therefore, only statement A is true about the relationship between data models and pivots.

Reference:
The Field Extractor (FX) is a tool that helps you extract fields from your data using delimiters or regular expressions. Delimiters are characters or strings that separate fields in your data. The FX can detect some common delimiters automatically, such as pipes (|), spaces ( ), commas (,), semicolons (;), etc. The FX cannot detect tabs (\t) as delimiters automatically, but you can specify them manually in the FX interface.

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The correct answer isD. Event types do not include a time range.
The explanation is as follows:
Event types are a categorization system that help you make sense of your data by matching events with
the same search string1.Event types are applied to events at search time and can be used as search terms
or filters12.
Saved reports are results savedfrom a search action that can show statistics and visualizations of
events3.Saved reports can be run anytime, and they fetch fresh results each time they are run34.Saved
reports can be shared with other users and added to dashboards4.
The main difference between event types and saved reports is that event types do not include a time
range, while saved reports do14.This means that event types can match events from any time period,
while saved reports are limited by the time range specified when they are created or run14.