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chore: Updating broken links for on demand transformation (#4759)
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docs/getting-started/concepts/dataset.md

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Dataset can be created from:
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1. Results of historical retrieval
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2. \[planned] Logging request (including input for [on demand transformation](../../reference/alpha-on-demand-feature-view.md)) and response during feature serving
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2. \[planned] Logging request (including input for [on demand transformation](../../reference/beta-on-demand-feature-view.md)) and response during feature serving
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3. \[planned] Logging features during writing to online store (from batch source or stream)
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### Creating a saved dataset from historical retrieval

docs/getting-started/concepts/feature-view.md

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**Note**: Feature views do not work with non-timestamped data. A workaround is to insert dummy timestamps.
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{% endhint %}
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A feature view is an object that represents a logical group of time-series feature data as it is found in a [data source](data-ingestion.md). Depending on the kind of feature view, it may contain some lightweight (experimental) feature transformations (see [\[Alpha\] On demand feature views](feature-view.md#alpha-on-demand-feature-views)).
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A **feature view** is defined as a *collection of features*.
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- In the online settings, this is a *stateful* collection of
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features that are read when the `get_online_features` method is called.
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- In the offline setting, this is a *stateless* collection of features that are created when the `get_historical_features`
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method is called.
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A feature view is an object representing a logical group of time-series feature data as it is found in a [data source](data-ingestion.md). Depending on the kind of feature view, it may contain some lightweight (experimental) feature transformations (see [\[Beta\] On demand feature views](../../reference/beta-on-demand-feature-view.md)).
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Feature views consist of:
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docs/getting-started/faq.md

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There are several kinds of transformations:
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* On demand transformations (See [docs](../reference/alpha-on-demand-feature-view.md))
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* On demand transformations (See [docs](../reference/beta-on-demand-feature-view.md))
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* These transformations are Pandas transformations run on batch data when you call `get_historical_features` and at online serving time when you call \`get\_online\_features.
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* Note that if you use push sources to ingest streaming features, these transformations will execute on the fly as well
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* Batch transformations (WIP, see [RFC](https://docs.google.com/document/d/1964OkzuBljifDvkV-0fakp2uaijnVzdwWNGdz7Vz50A/edit))

docs/tutorials/validating-historical-features.md

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return out
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```
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*Read more about on demand feature views [here](https://docs.feast.dev/reference/alpha-on-demand-feature-view)*
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*Read more about on demand feature views [here](../reference/beta-on-demand-feature-view.md)*
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```python

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