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Added TFL-based examples to the intro.

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debadair 2015-01-30 16:05:44 -08:00
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@ -15,3 +15,39 @@ Elasticsearch indexes in minutes--no code, no additional infrastructure required
=== Data Discovery and Visualization
Let's take a look at how you might use Kibana to explore and visualize data.
We've indexed some data from Transport for London (TFL) that shows a week's
worth of transit (Oyster) card usage.
From Kibana's Discover page, we can submit search queries, filter the results, and
examine the data in the returned documents. For example, we could search for all
of the trips that ended at the Baker Street station:
image::images/TFL-BakerStreet.jpg[Discover]
Right away, we can see that more people exit at Baker Street between 10:00 PM and 1:00 AM
than any other time of day. By default, the Discover page shows a time-series chart
and the first 500 entries that match the search criteria. You can change the time
filter, interact with the chart to drill down into the data, and view the details
of particular documents. For more information about exploring your data from the
Discover page, see <<discover>>.
You can construct visualizations of your search results from the Visualization page.
Each visualization is associated with a search. For example, we can create a histogram
that shows the weekly London commute traffic via tube using a a search that excludes
incomplete trips and trips by bus. The Y-axis is the number of trips. The X-axis shows
the day and time. By adding a sub-aggregation, we can see the top 3 end stations during
each hour:
image::images/TFL-CommuteHistogram.jpg[Visualize]
You can save and share visualizations and add them to dashboards to make it easy
to monitor and share particular metrics. For example, we could create a dashboard
that displays several visualizations of the TFL data:
image::images/TFL-Dashboard.jpg[Dashboard]
For more information about creating and sharing visualizations, see <<visualize>>.
For more information about working with Dashboards, see <<dashboard>>.