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1 change: 1 addition & 0 deletions .github/workflows/project-assigner.yml
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issue-mappings: |
[
{"label": "Feature:Lens", "projectNumber": 32, "columnName": "Long-term goals"},
{"label": "Feature:Discover", "projectNumber": 44, "columnName": "Inbox"},
{"label": "Feature:Canvas", "projectNumber": 38, "columnName": "Inbox"},
{"label": "Feature:Dashboard", "projectNumber": 68, "columnName": "Inbox"},
{"label": "Feature:Drilldowns", "projectNumber": 68, "columnName": "Inbox"},
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<!-- Do not edit this file. It is automatically generated by API Documenter. -->

[Home](./index.md) &gt; [kibana-plugin-plugins-data-public](./kibana-plugin-plugins-data-public.md) &gt; [IndexPatternType](./kibana-plugin-plugins-data-public.indexpatterntype.md)

## IndexPatternType enum

<b>Signature:</b>

```typescript
export declare enum IndexPatternType
```

## Enumeration Members

| Member | Value | Description |
| --- | --- | --- |
| DEFAULT | <code>&quot;default&quot;</code> | |
| ROLLUP | <code>&quot;rollup&quot;</code> | |

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Expand Up @@ -15,4 +15,5 @@ export interface TypeMeta
| Property | Type | Description |
| --- | --- | --- |
| [aggs](./kibana-plugin-plugins-data-public.indexpatterntypemeta.aggs.md) | <code>Record&lt;string, AggregationRestrictions&gt;</code> | |
| [params](./kibana-plugin-plugins-data-public.indexpatterntypemeta.params.md) | <code>{</code><br/><code> rollup_index: string;</code><br/><code> }</code> | |

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<!-- Do not edit this file. It is automatically generated by API Documenter. -->

[Home](./index.md) &gt; [kibana-plugin-plugins-data-public](./kibana-plugin-plugins-data-public.md) &gt; [IndexPatternTypeMeta](./kibana-plugin-plugins-data-public.indexpatterntypemeta.md) &gt; [params](./kibana-plugin-plugins-data-public.indexpatterntypemeta.params.md)

## IndexPatternTypeMeta.params property

<b>Signature:</b>

```typescript
params?: {
rollup_index: string;
};
```
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| --- | --- |
| [BUCKET\_TYPES](./kibana-plugin-plugins-data-public.bucket_types.md) | |
| [ES\_FIELD\_TYPES](./kibana-plugin-plugins-data-public.es_field_types.md) | \* |
| [IndexPatternType](./kibana-plugin-plugins-data-public.indexpatterntype.md) | |
| [KBN\_FIELD\_TYPES](./kibana-plugin-plugins-data-public.kbn_field_types.md) | \* |
| [METRIC\_TYPES](./kibana-plugin-plugins-data-public.metric_types.md) | |
| [QuerySuggestionTypes](./kibana-plugin-plugins-data-public.querysuggestiontypes.md) | |
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Expand Up @@ -19,6 +19,7 @@ export interface QuerySuggestionGetFnArgs
| [boolFilter](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.boolfilter.md) | <code>any</code> | |
| [indexPatterns](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.indexpatterns.md) | <code>IIndexPattern[]</code> | |
| [language](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.language.md) | <code>string</code> | |
| [method](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.method.md) | <code>ValueSuggestionsMethod</code> | |
| [query](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.query.md) | <code>string</code> | |
| [selectionEnd](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.selectionend.md) | <code>number</code> | |
| [selectionStart](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.selectionstart.md) | <code>number</code> | |
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<!-- Do not edit this file. It is automatically generated by API Documenter. -->

[Home](./index.md) &gt; [kibana-plugin-plugins-data-public](./kibana-plugin-plugins-data-public.md) &gt; [QuerySuggestionGetFnArgs](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.md) &gt; [method](./kibana-plugin-plugins-data-public.querysuggestiongetfnargs.method.md)

## QuerySuggestionGetFnArgs.method property

<b>Signature:</b>

```typescript
method?: ValueSuggestionsMethod;
```
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Expand Up @@ -39,5 +39,5 @@ export declare class Execution<Input = unknown, Output = unknown, InspectorAdapt
| [invokeChain(chainArr, input)](./kibana-plugin-plugins-expressions-public.execution.invokechain.md) | | |
| [invokeFunction(fn, input, args)](./kibana-plugin-plugins-expressions-public.execution.invokefunction.md) | | |
| [resolveArgs(fnDef, input, argAsts)](./kibana-plugin-plugins-expressions-public.execution.resolveargs.md) | | |
| [start(input)](./kibana-plugin-plugins-expressions-public.execution.start.md) | | Call this method to start execution.<!-- -->N.B. <code>input</code> is initialized to <code>null</code> rather than <code>undefined</code> for legacy reasons, because in legacy interpreter it was set to <code>null</code> by default. |
| [start(input, isSubExpression)](./kibana-plugin-plugins-expressions-public.execution.start.md) | | Call this method to start execution.<!-- -->N.B. <code>input</code> is initialized to <code>null</code> rather than <code>undefined</code> for legacy reasons, because in legacy interpreter it was set to <code>null</code> by default. |

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<b>Signature:</b>

```typescript
start(input?: Input): Observable<ExecutionResult<Output | ExpressionValueError>>;
start(input?: Input, isSubExpression?: boolean): Observable<ExecutionResult<Output | ExpressionValueError>>;
```

## Parameters

| Parameter | Type | Description |
| --- | --- | --- |
| input | <code>Input</code> | |
| isSubExpression | <code>boolean</code> | |

<b>Returns:</b>

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Expand Up @@ -39,5 +39,5 @@ export declare class Execution<Input = unknown, Output = unknown, InspectorAdapt
| [invokeChain(chainArr, input)](./kibana-plugin-plugins-expressions-server.execution.invokechain.md) | | |
| [invokeFunction(fn, input, args)](./kibana-plugin-plugins-expressions-server.execution.invokefunction.md) | | |
| [resolveArgs(fnDef, input, argAsts)](./kibana-plugin-plugins-expressions-server.execution.resolveargs.md) | | |
| [start(input)](./kibana-plugin-plugins-expressions-server.execution.start.md) | | Call this method to start execution.<!-- -->N.B. <code>input</code> is initialized to <code>null</code> rather than <code>undefined</code> for legacy reasons, because in legacy interpreter it was set to <code>null</code> by default. |
| [start(input, isSubExpression)](./kibana-plugin-plugins-expressions-server.execution.start.md) | | Call this method to start execution.<!-- -->N.B. <code>input</code> is initialized to <code>null</code> rather than <code>undefined</code> for legacy reasons, because in legacy interpreter it was set to <code>null</code> by default. |

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Expand Up @@ -11,14 +11,15 @@ N.B. `input` is initialized to `null` rather than `undefined` for legacy reasons
<b>Signature:</b>

```typescript
start(input?: Input): Observable<ExecutionResult<Output | ExpressionValueError>>;
start(input?: Input, isSubExpression?: boolean): Observable<ExecutionResult<Output | ExpressionValueError>>;
```

## Parameters

| Parameter | Type | Description |
| --- | --- | --- |
| input | <code>Input</code> | |
| isSubExpression | <code>boolean</code> | |

<b>Returns:</b>

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112 changes: 56 additions & 56 deletions docs/getting-started/quick-start-guide.asciidoc
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Expand Up @@ -7,7 +7,7 @@ When you've finished, you'll know how to:

* <<explore-the-data,Explore the data with *Discover*.>>

* <<view-and-analyze-the-data,Gain insight into the data with *Dashboard*.>>
* <<view-and-analyze-the-data,Analyze the data with *Dashboard*.>>

[float]
=== Required privileges
Expand All @@ -24,125 +24,125 @@ include::{docs-root}/shared/cloud/ess-getting-started.asciidoc[]
[[gs-get-data-into-kibana]]
== Add the sample data

Sample data sets come with sample visualizations, dashboards, and more to help you explore {kib} without adding your own data.
Sample data sets come with sample visualizations, dashboards, and more to help you explore {kib} before you ingest or add your own data.

. From the home page, click *Try our sample data*.
. On the home page, click *Try our sample data*.

. On the *Sample eCommerce orders* card, click *Add data*.
+
[role="screenshot"]
image::getting-started/images/add-sample-data.png[Add data UI]
image::images/add-sample-data.png[Add data UI for the sample data sets]

[float]
[[explore-the-data]]
== Explore the data

*Discover* displays an interactive histogram that shows the distribution of of data, or documents, over time, and a table that lists the fields for each document that matches the index. By default, all fields are shown for each matching document.
*Discover* displays the data in an interactive histogram that shows the distribution of data, or documents, over time, and a table that lists the fields for each document that matches the index pattern. To view a subset of the documents, you can apply filters to the data, and customize the table to display only the fields you want to explore.

. Open the main menu, then click *Discover*.

. Change the <<set-time-filter, time filter>> to *Last 7 days*.
+
[role="screenshot"]
image::images/tutorial-discover-2.png[]
image::images/tutorial-discover-2.png[Time filter menu with Last 7 days filter configured]

. To focus in on the documents you want to view, use the <<kuery-query,{kib} Query Language>>. In the *KQL* search field, enter:
. To view the sales orders for women's clothing that are $60 or more, use the <<kuery-query,*KQL*>> search field:
+
[source,text]
products.taxless_price >= 60 AND category : Women's Clothing
+
The query returns the women's clothing orders for $60 and more.
products.taxless_price >= 60 and category : Women's Clothing
+
[role="screenshot"]
image::images/tutorial-discover-4.png[]
image::images/tutorial-discover-4.png[Discover tables that displays only the orders for women's clothing that are $60 or more]

. Hover over the list of *Available fields*, then click *+* next to the fields you want to view in the table.
+
For example, when you add the *category* field, the table displays the product categories for the orders.
. To view only the product categories that contain sales orders, hover over the *category* field, then click *+*.
+
[role="screenshot"]
image::images/tutorial-discover-3.png[]
+
For more information, refer to <<discover, *Discover*>>.
image::images/tutorial-discover-3.png[Discover table that displays only the product categories that contain orders]

[float]
[[view-and-analyze-the-data]]
== View and analyze the data

A dashboard is a collection of panels that you can use to view and analyze the data. Panels contain visualizations, interactive controls, Markdown, and more.
A dashboard is a collection of panels that you can use to view and analyze the data. Panels contain visualizations, interactive controls, text, and more.

. Open the main menu, then click *Dashboard*.

. Click *[eCommerce] Revenue Dashboard*.
+
[role="screenshot"]
image::getting-started/images/tutorial-sample-dashboard.png[]
image::getting-started/images/tutorial-sample-dashboard.png[The [eCommerce] Revenue Dashboard that comes with the Sample eCommerce order data set]

[float]
[[filter-and-query-the-data]]
=== Filter the data
[[create-a-visualization]]
=== Create a visualization panel

Create a treemap panel that shows the top sales regions and manufacturers, then add the panel to the dashboard.

To focus in on the data you want to view on the dashboard, use filters.
. From the toolbar, click *Edit*, then click *Create visualzation*.

. From the *[eCommerce] Controls* panel, make a selection from the *Manufacturer* and *Category* dropdowns, then click *Apply changes*.
. Open the *Chart type* menu, then select *Treemap*.
+
For example, the following dashboard shows the data for women's clothing from Gnomehouse.
[role="screenshot"]
image::getting-started/images/tutorial-visualization-dropdown.png[Chart type menu with Treemap selected]

. From the *Available fields* list, drag and drop the following fields onto the workspace:

* *geoip.city_name*

* *manufacturer.keyword*
+
[role="screenshot"]
image::getting-started/images/tutorial-sample-filter.png[]
image::getting-started/images/tutorial-visualization-treemap.png[Treemap that displays Top values of geoip.city_name and Top values or manufacturer.keyword fields]

. To manually add a filter, click *Add filter*, then specify the options.
. Click *Save and return*.
+
For example, to view the orders for Wednesday, select *day_of_week* from the *Field* dropdown, select *is* from the *Operator* dropdown, then select *Wednesday* from the *Value* dropdown.
The treemap appears as the last visualization panel on the dashboard.
+
[role="screenshot"]
image::getting-started/images/tutorial-sample-filter2.png[]
image::getting-started/images/tutorial-final-dashboard.gif[Final dashboard with new treemap visualization]

[float]
[[interact-with-the-data]]
=== Interact with the data

You can interact with the dashboard data using controls that allow you to apply dashboard-level filters. Interact with the *[eCommerce] Controls* panel to view the women's clothing data from the Gnomehouse manufacturer.

. When you are done, remove the filters.
. From the *Manufacturer* dropdown, select *Gnomehouse*.

. From the *Category* dropdown, select *Women's Clothing*.

. Click *Apply changes*.
+
For more information, refer to <<dashboard,*Dashboard*>>.
[role="screenshot"]
image::getting-started/images/tutorial-sample-filter.png[The [eCommerce] Revenue Dashboard that shows only the women's clothing data from the Gnomehouse manufacturer]

[float]
[[create-a-visualization]]
=== Create a visualization panel

Create a treemap panel that shows the top regions and manufacturers, then add the panel to the dashboard.
[[filter-and-query-the-data]]
=== Filter the data

. From the toolbar, click *Edit*, then click *Create new*.
To view a subset of the data, you can apply filters to the dashboard panels. Apply a filter to view the women's clothing data generated on Wednesday from the Gnomehouse manufacturer.

. On the *New Visualization* window, click *Lens*.
. Click *Add filter*.

. From the *Available fields* list, drag and drop the following fields to the visualization builder:
. From the *Field* dropdown, select *day_of_week*.

* *geoip.city_name*
. From the *Operator* dropdown, select *is*.

* *manufacturer.keyword*
+
. From the visualization dropdown, select *Treemap*.
+
[role="screenshot"]
image::getting-started/images/tutorial-visualization-dropdown.png[Visualization dropdown with Treemap selected]
. From the *Value* dropdown, select *Wednesday*.

. Click *Save*.

. On the *Save Lens visualization*, enter a title and make sure *Add to Dashboard after saving* is selected, then click *Save and return*.
+
The treemap appears as the last visualization panel on the dashboard.
+
[role="screenshot"]
image::getting-started/images/tutorial-final-dashboard.gif[Final dashboard with new treemap visualization]
+
For more information, refer to <<dashboard,Dashboard>>.
image::getting-started/images/tutorial-sample-filter2.png[The [eCommerce] Revenue Dashboard that shows only the women's clothing data generated on Wednesday from the Gnomehouse manufacturer]

[float]
[[quick-start-whats-next]]
== What's next?

If you are you ready to add your own data, refer to <<connect-to-elasticsearch,Add data to {kib}>>.
*Add your own data.* Ready to add your own data? Go to {fleet-guide}/fleet-quick-start.html[Quick start: Get logs and metrics into the Elastic Stack] to learn how to ingest your data, or go to <<connect-to-elasticsearch,Add data to {kib}>> and learn about all the other ways you can add data.

If you want to ingest your data, refer to {fleet-guide}/fleet-quick-start.html[Quick start: Get logs and metrics into the Elastic Stack].
*Explore your own data in Discover.* Ready to learn more about exploring your data in *Discover*? Go to <<discover, Discover>>.

If you want to secure access to your data, refer to our guide on <<tutorial-secure-access-to-kibana, securing {kib}>>
*Create a dashboard with your own data.* Ready to learn more about analyzing your data in *Dashboard*? Go to <<dashboard, Dashboard>>.

If you want to try out {ml-features} with the sample data sets, refer to
{ml-docs}/ml-getting-started.html[Getting started with {ml}].
*Try out the {ml-features}.* Ready to analyze the sample data sets and generate models for its patterns of behavior? Go to {ml-docs}/ml-getting-started.html[Getting started with {ml}].
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