Small fixes for example documentation (#48)

Co-authored-by: Christoph Böhm <[email protected]>

docs/docs/user/examples/real-time-customer-profiles.md

@@ -18,7 +18,6 @@ The code can be found in [Quick's example repository](https://github.com/bakdata
 The example uses the real world data set [LFM-1b](http://www.cp.jku.at/datasets/LFM-1b/).
 The Kafka Streams application is written based on our open source [streams-bootstrap library](https://github.com/bakdata/streams-bootstrap).
 
----
 
 Finally, there is a video explaining this example:
 <div class="video-wrapper">
@@ -28,7 +27,7 @@ Finally, there is a video explaining this example:
         title="YouTube video player" width="900" height="500" ></iframe>
 </div>
 
-## The Input: Listening Events
+## Input: Listening events
 
 Every time a customer listens to a song, the system emits a listening event containing the ids of album, artist and track.
 The system additionally attaches metadata such as the timestamp to the event.
@@ -42,12 +41,12 @@ Later, a Kafka Streams application processes it for the customer profile creatio
 {"userId": 1335, "artistId": 13866, "albumId": 29007, "trackId": 83201, "timestamp": 1568052385}
 ```
 
-## The Quick Configuration
+## Quick configuration
 
-### The Global GraphQL Schema
+### Global GraphQL schema
 
 First, define the global schema with GraphQL.
-The query called `getUserProfile` combines six metrics of the customer profile:
+The query called `getUserProfile` combines six metrics for the customer profile:
 
 - total listening events
 - the first and last time a user listened to a song
@@ -160,15 +159,13 @@ The user profile has the following metrics:
 - total number of listening events
 
 1. Create topics that later store the corresponding data:
-
     ```shell
     quick topic create firstlisten --key long --value long
     quick topic create lastlisten --key long --value long
     quick topic create counts --key long --value long
     ```
 
 2. Deploy the applications:
-
     ```shell
     quick app deploy firstlisten \
     --registry bakdata \

docs/docs/user/examples/real-time-monitoring.md

@@ -1,31 +1,28 @@
 # Real-time monitoring and analytics
 
-This use case demonstrates how Quick can be used to process data streams
-and consume the results to build live dashboards.
+This use case demonstrates how Quick can be used to process data streams and consume the results to build live dashboards.
 For that, we consider the example of a car-sharing company.
 Their fleet of cars drives around the city.
-All of them emit statuses that, among others, include the trip's and vehicle's ids
-as well as the car's current position and battery level.
+All of them emit statuses that, among others, include the trip's and vehicle's ids as well as the car's current position and battery level.
+
+## What this will demonstrate
+
+- aggregations on an incoming stream
+- how to join topic data at query-time
+- subscriptions in action
+- the ingest REST API used by an example producer
+
 A [dashboard](https://carsharing.d9p.io/) displays this information on an interactive map.
 
 [![carsharing-app](../../assets/images/carsharing.png)](https://carsharing.d9p.io/)
 
----
 <div class="video-wrapper">
 <iframe allow="accelerometer; autoplay;
                 clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen
         src="https://www.youtube-nocookie.com/embed/fJz-Rasp7fE"
         title="YouTube video player" width="900" height="500" ></iframe>
 </div>
 
---- 
-
-## What this will demonstrate
-
-- the deployment of an aggregating application
-- how to join topic data at query-time
-- the usage of subscriptions
-- the ingestion of demo data into your system
 
 ## Apache Kafka and data processing