57 lines
2.8 KiB
Plaintext
57 lines
2.8 KiB
Plaintext
[[introduction]]
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== Introduction
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Kibana is an open source analytics and visualization platform designed to work with Elasticsearch. You use Kibana to
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search, view, and interact with data stored in Elasticsearch indices. You can easily perform advanced data analysis
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and visualize your data in a variety of charts, tables, and maps.
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Kibana makes it easy to understand large volumes of data. Its simple, browser-based interface enables you to quickly
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create and share dynamic dashboards that display changes to Elasticsearch queries in real time.
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Setting up Kibana is a snap. You can install Kibana and start exploring your Elasticsearch indices in minutes -- no
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code, no additional infrastructure required.
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For more information about creating and sharing visualizations and dashboards, see the <<visualize, Visualize>>
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and <<dashboard, Dashboard>> topics. A complete <<getting-started,tutorial>> covering several aspects of Kibana's
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functionality is also available.
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NOTE: This guide describes how to use Kibana {version}. For information about what's new in Kibana {version}, see
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the <<releasenotes, release notes>>.
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////
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[float]
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[[data-discovery]]
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=== Data Discovery and Visualization
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Let's take a look at how you might use Kibana to explore and visualize data.
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We've indexed some data from Transport for London (TFL) that shows one week
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of transit (Oyster) card usage.
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From Kibana's Discover page, we can submit search queries, filter the results, and
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examine the data in the returned documents. For example, we can get all trips
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completed by the Tube during the week by excluding incomplete trips and trips by bus:
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image:images/TFL-CompletedTrips.jpg[Discover]
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Right away, we can see the peaks for the morning and afternoon commute hours in the
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histogram. By default, the Discover page also shows the first 500 entries that match the
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search criteria. You can change the time filter, interact with the histogram to drill
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down into the data, and view the details of particular documents. For more
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information about exploring your data from the Discover page, see <<discover, Discover>>.
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You can construct visualizations of your search results from the Visualization page.
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Each visualization is associated with a search. For example, we can create a histogram
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that shows the weekly London commute traffic via the Tube using our previous search.
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The Y-axis shows the number of trips. The X-axis shows
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the day and time. By adding a sub-aggregation, we can see the top 3 end stations during
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each hour:
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image:images/TFL-CommuteHistogram.jpg[Visualize]
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You can save and share visualizations and combine them into dashboards to make it easy
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to correlate related information. For example, we could create a dashboard
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that displays several visualizations of the TFL data:
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image:images/TFL-Dashboard.jpg[Dashboard]
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////
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