undo some doc changes

docs/maps/asset-tracking-tutorial.asciidoc

@@ -156,16 +156,16 @@ image::maps/images/asset-tracking-tutorial/logstash_output.png[]
 . Leave the terminal window open and Logstash running throughout this tutorial.
 
 [float]
-==== Step 3: Create a data view for the tri_met_tracks {es} index
+==== Step 3: Create a {kib} index pattern for the tri_met_tracks {es} index
 
-. In Kibana, open the main menu, and click *Stack Management > Data views*.
-. Click *Create data view*.
-. Give the data view a name: *tri_met_tracks**.
+. In Kibana, open the main menu, and click *Stack Management > Index Patterns*.
+. Click *Create index pattern*.
+. Give the index pattern a name: *tri_met_tracks**.
 . Click *Next step*.
 . Set the *Time field* to *time*.
-. Click *Create data view*.
+. Click *Create index pattern*.
 
-{kib} shows the fields in your data view.
+{kib} shows the fields in your index pattern.
 
 [role="screenshot"]
 image::maps/images/asset-tracking-tutorial/index_pattern.png[]
@@ -174,7 +174,7 @@ image::maps/images/asset-tracking-tutorial/index_pattern.png[]
 ==== Step 4: Explore the Portland bus data
 
 . Open the main menu, and click *Discover*.
-. Set the data view to *tri_met_tracks**.
+. Set the index pattern to *tri_met_tracks**.
 . Open the <<set-time-filter, time filter>>, and set the time range to the last 15 minutes.
 . Expand a document and explore some of the fields that you will use later in this tutorial: `bearing`, `in_congestion`, `location`, and `vehicle_id`.
 
@@ -202,7 +202,7 @@ Add a layer to show the bus routes for the last 15 minutes.
 
 . Click *Add layer*.
 . Click *Tracks*.
-. Select the *tri_met_tracks** data view.
+. Select the *tri_met_tracks** index pattern.
 . Define the tracks:
 .. Set *Entity* to *vehicle_id*.
 .. Set *Sort* to *time*.
@@ -225,7 +225,7 @@ image::maps/images/asset-tracking-tutorial/tracks_layer.png[]
 Add a layer that uses attributes in the data to set the style and orientation of the buses. You’ll see the direction buses are headed and what traffic is like.
 
 . Click *Add layer*, and then select *Top Hits per entity*.
-. Select the *tri_met_tracks** data view.
+. Select the *tri_met_tracks** index pattern.
 . To display the most recent location per bus:
 .. Set *Entity* to *vehicle_id*.
 .. Set *Documents per entity* to 1.

docs/maps/geojson-upload.asciidoc

@@ -30,11 +30,11 @@ a preview of the data on the map.
 . Use the default *Index type* of {ref}/geo-point.html[geo_point] for point data,
 or override it and select {ref}/geo-shape.html[geo_shape].
 All other shapes will default to a type of `geo_shape`.
-. Leave the default *Index name* and *Data view* names (the name of the uploaded
+. Leave the default *Index name* and *Index pattern* names (the name of the uploaded
 file minus its extension). You might need to change the index name if it is invalid.
 . Click *Import file*.
 +
-Upon completing the indexing process and creating the associated data view,
+Upon completing the indexing process and creating the associated index pattern,
 the Elasticsearch responses are shown on the *Layer add panel* and the indexed data
 appears on the map. The geospatial data on the map
 should be identical to the locally-previewed data, but now it's indexed data from Elasticsearch.

docs/maps/indexing-geojson-data-tutorial.asciidoc

@@ -58,8 +58,8 @@ auto-populate *Index type* with either {ref}/geo-point.html[geo_point] or
 . Click *Import file*.
 +
 You'll see activity as the GeoJSON Upload utility creates a new index
-and data view for the data set. When the process is complete, you should
-receive messages that the creation of the new index and data view
+and index pattern for the data set. When the process is complete, you should
+receive messages that the creation of the new index and index pattern
 were successful.
 
 . Click *Add layer*.
@@ -88,6 +88,11 @@ lightning strikes is that you can perform aggregations on the data.
 
 . Click *Add layer*.
 . From the list of layer types, click *Heat map*.
++
+Because you indexed `lightning_detected.geojson` using the index name and
+pattern `lightning_detected`, that data is available as a {ref}/geo-point.html[geo_point]
+aggregation.
+
 . Select `lightning_detected`.
 . Click *Add layer* to add the heat map layer
 "Lightning intensity".

docs/maps/maps-aggregations.asciidoc

@@ -62,7 +62,7 @@ To enable a grid aggregation layer:
 To enable a blended layer that dynamically shows clusters or documents:
 
 . Click *Add layer*, then select the *Documents* layer.
-. Configure *Data view* and the *Geospatial field*.
+. Configure *Index pattern* and the *Geospatial field*.
 . In *Scaling*, select *Show clusters when results exceed 10000*.
 
 
@@ -77,7 +77,7 @@ then accumulates the most relevant documents based on sort order for each entry
 To enable top hits:
 
 . Click *Add layer*, then select the *Top hits per entity* layer.
-. Configure *Data view* and *Geospatial field*.
+. Configure *Index pattern* and *Geospatial field*.
 . Set *Entity* to the field that identifies entities in your documents.
 This field will be used in the terms aggregation to group your documents into entity buckets.
 . Set *Documents per entity* to configure the maximum number of documents accumulated per entity.

docs/maps/maps-getting-started.asciidoc

@@ -49,7 +49,7 @@ and lighter shades will symbolize countries with less traffic.
 . From the **Layer** dropdown menu, select **World Countries**.
 
 . In **Statistics source**, set:
-** **Data view** to **kibana_sample_data_logs**
+** **Index pattern** to **kibana_sample_data_logs**
 ** **Join field** to **geo.dest**
 
 . Click **Add layer**.
@@ -95,7 +95,7 @@ The layer is only visible when users zoom in.
 
 . Click **Add layer**, and then click **Documents**.
 
-. Set **Data view** to **kibana_sample_data_logs**.
+. Set **Index pattern** to **kibana_sample_data_logs**.
 
 . Set **Scaling** to *Limits results to 10000.*
 
@@ -129,7 +129,7 @@ more total bytes transferred, and smaller circles will symbolize
 grids with less bytes transferred.
 
 . Click **Add layer**, and select **Clusters and grids**.
-. Set **Data view** to **kibana_sample_data_logs**.
+. Set **Index pattern** to **kibana_sample_data_logs**.
 . Click **Add layer**.
 . In **Layer settings**, set:
 ** **Name** to `Total Requests and Bytes`

docs/maps/reverse-geocoding-tutorial.asciidoc

@@ -141,7 +141,7 @@ PUT kibana_sample_data_logs/_settings
 ----------------------------------
 
 . Open the main menu, and click *Discover*.
-. Set the data view to *kibana_sample_data_logs*.
+. Set the index pattern to *kibana_sample_data_logs*.
 . Open the <<set-time-filter, time filter>>, and set the time range to the last 30 days.
 . Scan through the list of *Available fields* until you find the `csa.GEOID` field. You can also search for the field by name.
 . Click image:images/reverse-geocoding-tutorial/add-icon.png[Add icon] to toggle the field into the document table.
@@ -162,10 +162,10 @@ Now that our web traffic contains CSA region identifiers, you'll visualize CSA r
 . Click *Choropleth*.
 . For *Boundaries source*: 
 .. Select *Points, lines, and polygons from Elasticsearch*.
-.. Set *Data view* to *csa*.
+.. Set *Index pattern* to *csa*.
 .. Set *Join field* to *GEOID*.
 . For *Statistics source*:
-.. Set *Data view* to *kibana_sample_data_logs*.
+.. Set *Index pattern* to *kibana_sample_data_logs*.
 .. Set *Join field* to *csa.GEOID.keyword*.
 . Click *Add layer*.
 . Scroll to *Layer Style* and Set *Label* to *Fixed*.

docs/maps/trouble-shooting.asciidoc

@@ -24,15 +24,15 @@ image::maps/images/inspector.png[]
 ==== Index not listed when adding layer
 
 * Verify your geospatial data is correctly mapped as {ref}/geo-point.html[geo_point] or {ref}/geo-shape.html[geo_shape].
-  ** Run `GET myDataViewTitle/_field_caps?fields=myGeoFieldName` in <<console-kibana, Console>>, replacing `myDataViewTitle` and `myGeoFieldName` with your data view title and geospatial field name.
+  ** Run `GET myIndexPatternTitle/_field_caps?fields=myGeoFieldName` in <<console-kibana, Console>>, replacing `myIndexPatternTitle` and `myGeoFieldName` with your index pattern title and geospatial field name.
   ** Ensure response specifies `type` as `geo_point` or `geo_shape`.
-* Verify your geospatial data is correctly mapped in your <<managing-fields, data view>>.
-  ** Open your data view in <<management, Stack Management>>.
+* Verify your geospatial data is correctly mapped in your <<managing-fields,index pattern>>.
+  ** Open your index pattern in <<management, Stack Management>>.
   ** Ensure your geospatial field type is `geo_point` or `geo_shape`.
   ** Ensure your geospatial field is searchable and aggregatable.
   ** If your geospatial field type does not match your Elasticsearch mapping, click the *Refresh* button to refresh the field list from Elasticsearch.
-* Data views with thousands of fields can exceed the default maximum payload size.
-Increase <<settings, `server.maxPayload`>> for large data views.
+* Index patterns with thousands of fields can exceed the default maximum payload size.
+Increase <<settings, `server.maxPayload`>> for large index patterns.
 
 [float]
 ==== Features are not displayed

docs/maps/vector-tooltips.asciidoc

@@ -18,7 +18,7 @@ image::maps/images/multifeature_tooltip.png[]
 ==== Format tooltips
 
 You can format the attributes in a tooltip by adding <<managing-fields, field formatters>> to your
-data view. You can use field formatters to round numbers, provide units,
+index pattern. You can use field formatters to round numbers, provide units,
 and even display images in your tooltip.
 
 [float]

docs/user/alerting/rule-types/es-query.asciidoc

@@ -17,7 +17,7 @@ Define properties to detect the condition.
 [role="screenshot"]
 image::user/alerting/images/rule-types-es-query-conditions.png[Five clauses define the condition to detect]
 
-Index:: This clause requires an *index or {data-source}* and a *time field* that will be used for the *time window*.
+Index:: This clause requires an *index or index pattern* and a *time field* that will be used for the *time window*.
 Size:: This clause specifies the number of documents to pass to the configured actions when the the threshold condition is met.
 {es} query:: This clause specifies the ES DSL query to execute. The number of documents that match this query will be evaluated against the threshold
 condition. Aggregations are not supported at this time. 

docs/user/alerting/rule-types/geo-rule-types.asciidoc

@@ -10,17 +10,17 @@ In the event that an entity is contained within a boundary, an alert may be gene
 ==== Requirements
 To create a Tracking containment rule, the following requirements must be present:
 
-- *Tracks index or {data-source}*: An index containing a `geo_point` field, `date` field,
+- *Tracks index or index pattern*: An index containing a `geo_point` field, `date` field,
 and some form of entity identifier. An entity identifier is a `keyword` or `number`
 field that consistently identifies the entity to be tracked. The data in this index should be dynamically
 updating so that there are entity movements to alert upon.
-- *Boundaries index or {data-source}*: An index containing `geo_shape` data, such as boundary data and bounding box data.
+- *Boundaries index or index pattern*: An index containing `geo_shape` data, such as boundary data and bounding box data.
 This data is presumed to be static (not updating). Shape data matching the query is
 harvested once when the rule is created and anytime after when the rule is re-enabled
 after disablement.
 
 By design, current interval entity locations (_current_ is determined by `date` in
-the *Tracked index or {data-source}*) are queried to determine if they are contained
+the *Tracked index or index pattern*) are queried to determine if they are contained
 within any monitored boundaries. Entity
 data should be somewhat "real time", meaning the dates of new documents aren’t older
 than the current time minus the amount of the interval. If data older than
@@ -39,13 +39,13 @@ as well as 2 Kuery bars used to provide additional filtering context for each of
 [role="screenshot"]
 image::user/alerting/images/alert-types-tracking-containment-conditions.png[Five clauses define the condition to detect]
 
-Index (entity):: This clause requires an *index or {data-source}*, a *time field* that will be used for the *time window*, and a *`geo_point` field* for tracking.
+Index (entity):: This clause requires an *index or index pattern*, a *time field* that will be used for the *time window*, and a *`geo_point` field* for tracking.
 When entity:: This clause specifies which crossing option to track. The values
 *Entered*, *Exited*, and *Crossed* can be selected to indicate which crossing conditions
 should trigger a rule. *Entered* alerts on entry into a boundary, *Exited* alerts on exit
 from a boundary, and *Crossed* alerts on all boundary crossings whether they be entrances
 or exits.
-Index (Boundary):: This clause requires an *index or {data-source}*, a *`geo_shape` field*
+Index (Boundary):: This clause requires an *index or index pattern*, a *`geo_shape` field*
 identifying boundaries, and an optional *Human-readable boundary name* for better alerting
 messages.
 

docs/user/alerting/rule-types/index-threshold.asciidoc

@@ -17,7 +17,7 @@ Define properties to detect the condition.
 [role="screenshot"]
 image::user/alerting/images/rule-types-index-threshold-conditions.png[Five clauses define the condition to detect]
 
-Index:: This clause requires an *index or {data-source}* and a *time field* that will be used for the *time window*.
+Index:: This clause requires an *index or index pattern* and a *time field* that will be used for the *time window*.
 When:: This clause specifies how the value to be compared to the threshold is calculated. The value is calculated by aggregating a numeric field a the *time window*. The aggregation options are: `count`, `average`, `sum`, `min`, and `max`. When using `count` the document count is used, and an aggregation field is not necessary. 
 Over/Grouped Over:: This clause lets you configure whether the aggregation is applied over all documents, or should be split into groups using a grouping field. If grouping is used, an  <<alerting-concepts-alerts, alert>> will be created for each group when it exceeds the threshold. To limit the number of alerts on high cardinality fields, you must specify the number of groups to check against the threshold. Only the *top* groups are checked.
 Threshold:: This clause defines a threshold value and a comparison operator  (one of `is above`, `is above or equals`, `is below`, `is below or equals`, or `is between`). The result of the aggregation is compared to this threshold.