Documentation: Add page about enumerating use cases

docs/source/index.rst

@@ -123,3 +123,4 @@ data streaming systems like `Apache Flink <https://flink.apache.org/>`_,
    async.rst
    plotting.rst
    plugins.rst
+   use-cases.rst

docs/source/use-cases.rst

@@ -0,0 +1,28 @@
+Use cases
+=========
+
+ETL applications
+----------------
+
+  In LorryStream_, we use Streamz at the core for relaying data from streaming
+  sources into CrateDB_, because we have been looking for something smaller
+  and more concise than Beam, Flink, or Spark. Streamz gives us the freedom
+  to use advanced stream processing and flow control primitives within Python
+  applications to feed databases, without the need to spin up compute clusters,
+  or deal with Java class paths.
+
+In this spirit, LorryStream is effectively just a humble CLI interface for
+Streamz.
+
+Telemetry readings
+------------------
+
+  At my company, we use it at two different points in our data processing to
+  create a disjoint subcover of a noisy stream of telemetry readings and then
+  blend in metadata from users and external authoritative resources to give
+  users an understanding of what (and what kinds of) events are happening in
+  their space.
+
+
+.. _CrateDB: https://github.com/crate/crate
+.. _LorryStream: https://lorrystream.readthedocs.io/