# Explore data
URL: https://docs.datarobot.com/en/docs/workbench/nxt-workbench/dataprep/explore-data/index.html

> The Data assets tile lists each dataset that has been added to your Use Case and provides the ability interact with those datasets, by exploring features, managing feature lists, wrangling data, or creating an experiment.

# Explore data

The Data assets tile lists all datasets and recipes currently linked to the selected Use Case. From here, you can manage your assets and launch various data actions:

|  | Element | Description |
| --- | --- | --- |
| (1) | Add Data | Click to open the Add data modal, allowing you to add datasets to the current Use Case. |
| (2) | Search | Search for a specific dataset. |
| (3) | Asset type icons | Each asset is preceded by one of the following icons: : Indicates that the asset is a registered dataset.: Indicates that the asset is a wrangling recipe. |
| (4) | Actions menu | Click the Actions menu to interact with a data asset.For datasets you can:Edit dataset name: Rename the dataset.Explore: View exploratory data insights and manage feature lists.Open in Wrangler: Perform data wrangling on datasets retrieved from a data connection.Open in SQL Editor: Use SQL queries to clean and prepare data.Feature Discovery: Perform Feature Discovery when working with two or more datasets.Start modeling: Set up an experiment using the dataset.Remove from Use Case: Remove the dataset from the Use Case, also removing access for any team members. The dataset is still available via the Data Registry.For recipes you can:Edit: Modify the wrangling recipe.Clone: Create a duplicate entry of the wrangling recipe.Remove from Use Case: Remove the recipe from the Use Case. |
| (5) | Sort | Sort the dataset columns. |

While a dataset is being registered in Workbench, DataRobot also performs exploratory data analysis [(EDA1)](https://docs.datarobot.com/en/docs/reference/data-ref/eda-explained.html#eda1) —analyzing and profiling every feature to detect feature types, automatically transform date-type features, and assess feature quality. Once registration is complete, you can explore the information uncovered while computing EDA1.

To open the data explore page, click the Actions menu next to the dataset you want to view and select Explore. Alternatively, click the dataset name to view its insights.

## Data explore tiles

| Tile | Description |
| --- | --- |
|  | Displays summary information for the dataset. |
|  | Displays a more visual representation of the features in your dataset, including frequent values. |
|  | Displays features in a table format alongside feature importance and summary statistics. Select specific features to view more detailed data insights than those shown on the Data preview tile. |
|  | Allows you to create new feature lists as well as manage existing ones. |

### Info tile

Displays summary information for the dataset version you're currently viewing.

The page reports:

| Field | Description |
| --- | --- |
| Created | A timestamp indicating the registration date of the dataset as well as the user who added the dataset to DataRobot. |
| Dataset | The name, number of features, and number of rows in the dataset. |
| Recipe | The name and recipe type used to create the dataset after being applied to the source data. |
| Modified | A timestamp indicating when the dataset was last modified as well as the user who modified the dataset. |
| Feature Summary | The number of features in the dataset, grouped by data type. |

If the dataset you're viewing is the output of a published wrangling recipe, you can click Recipe SQL at the bottom of the page to view the final compiled form of the operations executed by the data source.

### Data preview tile

Displays a preview using a uniform random sampling of the selected dataset (see [EDA insights](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/dataprep/explore-data/eda-insights.html) for more information). If the dataset is dynamic, you can view an interactive sample, in which case DataRobot displays a random sampling of the raw data. You can specify the sampling method and number of rows in the right panel under Interactive sample. This option is not available for snapshot datasets.

|  | Element | Description |
| --- | --- | --- |
| (1) | Show features from dropdown | Allows you to view features from a specific feature list. |
| (2) | + Create feature list | Creates a new feature list. |
| (3) | Search | Searches for a specific feature in the dataset or feature list you're currently viewing. |
| (4) | Features | Displays each feature row and column for the selected feature list. |
| (5) | Frequent values chart | Plots the counts of each individual value for the most frequent values of a feature. |
| (6) | Snapshot policy | Displays the selected dataset version. If the snapshot version is selected, DataRobot displays the date and time of the snapshot creation. Click the dropdown to access the following:Version history: An abbreviated version history that displays the dynamic dataset (live data) and most recent snapshot. + Create snapshot: Creates a snapshot of the dataset you're viewing. After registration is complete, the new snapshot is listed as the latest version, and can also be accessed in the Use Case and Data Registry. Select version: Opens Dataset Versions in the right panel. |
| (7) | Preview sample | Displays the number of rows used to generate the preview out of the total number of rows in the dataset. |
| (8) | Wrangling recipe | Allows you to view the wrangling recipe, if applicable, associated with the dataset, as well as continue wrangling the dataset. |

Select a feature to view additional summary statistics and insights.

|  | Element | Description |
| --- | --- | --- |
| (1) | Feature dropdown | Allows you to change the feature you're currently viewing. |
| (2) | Summary statistics | Displays summary statistics for the feature, including data quality issues and unique values. |
| (3) | Insights | Allows you to view available insights for the variable type of the feature. |
| (4) | Hover details | Displays additional information when you hover on the chart. |
| (5) | Go to feature | Opens the Features tile and expands the feature you were viewing. |

### Features tile

Displays each feature within the selected feature list. Click on a feature to view additional information, including summary metrics and frequent values. The [available insights](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/dataprep/explore-data/eda-insights.html#available-insights) are based on the variable type of the feature.

|  | Element | Description |
| --- | --- | --- |
| (1) | Show features from dropdown | Allows you to view features from a specific feature list. |
| (2) | + Create feature list | Creates a new feature list. |
| (3) | Search | Searches for a specific feature in the dataset or feature list you're currently viewing. |
| (4) | Features | Displays each feature, as well as summary statistics for each feature, in the selected feature list. |
| (5) | Snapshot policy | Displays the selected dataset version. If the snapshot version is selected, DataRobot displays the date and time of the snapshot's creation. Click the dropdown to access the following:Version history: An abbreviated version history that displays the dynamic dataset (live data) and most recent snapshot. + Create snapshot: Creates a snapshot of the dataset you're viewing. After registration is complete, the new snapshot is listed as the latest version, and can also be accessed in the Use Case and Data Registry. Select version: Opens Dataset Versions in the right panel. |
| (6) | Preview sample | Displays the number of rows used to generate the preview out of the total number of rows in the dataset. |
| (7) | Show summary | Displays the following summary information for the dataset: Name: The name of the dataset used to set up the experiment.Features: The number of features in the selected feature list. Rows: The number of rows in the dataset. Data Quality Assessment: Data quality issues detected by DataRobot during modeling as part of EDA1. |
| (8) | Wrangling recipe | Allows you to view the wrangling recipe, if applicable, associated with the dataset, as well as continue wrangling the dataset. |
| (9) | Create feature transformation | Allows you create a new feature by transforming an existing feature in the dataset. |

Select a feature to view additional summary statistics and insights:

|  | Element | Description |
| --- | --- | --- |
| (1) | Summary statistics | Displays summary statistics for the feature, including data quality issues and unique values. |
| (2) | Insights | Allows you to view available insights for the variable type of the feature. |
| (3) | Column management | Allows hide, display, pin, and reorder columns. |
| (4) | Create feature transformation | Allows you create a new feature by transforming an existing feature in the dataset. |

## Dataset versioning

The data explore page supports dataset versioning, allowing you to access a history of data snapshots as well as create new snapshots from the same page. Note that you can access dataset versioning from any view on the data explore page.

To access dataset versions, click the dropdown next to Data actions or open Dataset Versions in the right panel.

|  | Element | Description |
| --- | --- | --- |
| (1) | Snapshot policy | Displays the selected dataset version. If the snapshot version is selected, DataRobot displays the date and time of the snapshot creation. Click the dropdown to access the following:Version history: An abbreviated version history that displays the dynamic dataset (live data) and most recent snapshot. + Create snapshot: Creates a snapshot of the dataset you're viewing. After registration is complete, the new snapshot is listed as the latest version, and can also be accessed in the Use Case and Data Registry. Select version: Opens Dataset Versions in the right panel. |
| (2) | Dataset Versions | Displays a version history of the dataset. Click a dataset to view a different version. |
| (3) | + Create snapshot / Upload new version | Allows you to add additional versions of the dataset, and after registration is complete, the new dataset is displayed in the version history. Additionally, it is added to the Use Case and Data Registry. If the snapshot policy of the original dataset is dynamic or snapshot,the + Create snapshot button is available, which creates a snapshot of the dataset you're viewing.If the original dataset is static (i.e., uploaded as a local file), the Upload new version button is available, which allows you to upload updated local versions of the dataset. |

## Data actions

You can perform the following actions on the data explore page (note that these actions persist no matter what view is currently selected):

|  | Element | Description |
| --- | --- | --- |
| (1) | Dataset name | To rename the dataset, click on its name. To save your changes, click outside of the text field. |
| (2) | Data actions | Open the Data actions dropdown to perform one of the following actions with the dataset you're currently viewing:Start wrangling: Perform data wrangling on the dataset. Only available for dynamic datasets. Start modeling: Set up an experiment using the currently selected dataset version. By default, the latest version of the dataset is used.Start feature discovery: Use Feature Discovery to perform multi-dataset, interaction-based feature creationDownload dataset: Download the dataset locally. Only available for snapshotted datasets.Remove dataset: Remove the dataset from the Use Case. It will no longer be visible on the Data tab, however, it will be available in Data Registry and will not affect experiments created with the dataset. |
| (3) | Data Versions actions | Under Dataset Versions, click the Actions menu to perform one of the following actions on a specific snapshot dataset:Start modeling: Set up an experiment using this dataset.Download dataset: Download the dataset locally. Only available for snapshotted datasets.Delete: Removes the dataset from Version History, however, it will be available in Data Registry and will not affect experiments created with the dataset. |

## Next steps

From here, you can:

- Add more data.
- Perform data wrangling for datasets added via a data connection.
- Use the dataset to set up an experiment and start modeling.

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