kibana/docs/getting-started/quick-start-guide.asciidoc

147 lines
5.7 KiB
Plaintext

[[get-started]]
== Quick start
To quickly get up and running with {kib}, set up on Cloud, then add a sample data set that you can explore and analyze.
When you've finished, you'll know how to:
* <<explore-the-data,Explore the data with *Discover*.>>
* <<view-and-analyze-the-data,Analyze the data with *Dashboard*.>>
[float]
=== Required privileges
When security is enabled, you must have `read`, `write`, and `manage` privileges on the `kibana_sample_data_*` indices.
Learn how to <<tutorial-secure-access-to-kibana, secure access to {kib}>>, or refer to {ref}/security-privileges.html[Security privileges] for more information.
[float]
[[set-up-on-cloud]]
== Set up on cloud
include::{docs-root}/shared/cloud/ess-getting-started.asciidoc[]
[float]
[[gs-get-data-into-kibana]]
== Add the sample data
Sample data sets come with sample visualizations, dashboards, and more to help you explore {kib} before you ingest or add your own data.
. On the home page, click *Try our sample data*.
. On the *Sample eCommerce orders* card, click *Add data*.
+
[role="screenshot"]
image::images/addData_sampleDataCards_7.15.0.png[Add data UI for the sample data sets]
[float]
[[explore-the-data]]
== Explore the data
*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[Time filter menu with Last 7 days filter configured]
. 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
+
[role="screenshot"]
image::images/tutorial-discover-4.png[Discover tables that displays only the orders for women's clothing that are $60 or more]
. 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[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, text, and more.
. Open the main menu, then click *Dashboard*.
. Click *[eCommerce] Revenue Dashboard*.
+
[role="screenshot"]
image::images/dashboard_ecommerceRevenueDashboard_7.15.0.png[The [eCommerce] Revenue Dashboard that comes with the Sample eCommerce order data set]
[float]
[[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.
. In the toolbar, click *Edit*.
. On the dashboard, click *Create visualization*.
. In the drag-and-drop visualization editor, open the *Visualization type* dropdown, then select *Treemap*.
+
[role="screenshot"]
image::getting-started/images/tutorial-visualization-dropdown.png[Chart type menu with Treemap selected]
. From the *Available fields* list, drag the following fields to the workspace:
* *geoip.city_name*
* *manufacturer.keyword*
+
[role="screenshot"]
image::getting-started/images/tutorial-visualization-treemap.png[Treemap that displays Top values of geoip.city_name and Top values or manufacturer.keyword fields]
. Click *Save and return*.
+
The treemap appears as the last visualization panel on the dashboard.
[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.
. From the *Manufacturer* dropdown, select *Gnomehouse*.
. From the *Category* dropdown, select *Women's Clothing*.
. Click *Apply changes*.
+
[role="screenshot"]
image::images/dashboard_sampleDataFilter_7.15.0.png[The [eCommerce] Revenue Dashboard that shows only the women's clothing data from the Gnomehouse manufacturer]
[float]
[[filter-and-query-the-data]]
=== Filter the data
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.
. Click *Add filter*.
. From the *Field* dropdown, select *day_of_week*.
. From the *Operator* dropdown, select *is*.
. From the *Value* dropdown, select *Wednesday*.
. Click *Save*.
+
[role="screenshot"]
image::images/dashboard_sampleDataAddFilter_7.15.0.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?
*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.
*Explore your own data in Discover.* Ready to learn more about exploring your data in *Discover*? Go to <<discover, Discover>>.
*Create a dashboard with your own data.* Ready to learn more about analyzing your data in *Dashboard*? Go to <<dashboard, Dashboard>>.
*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}].