[airflow] 11/44: Revise "Project Focus" copy (#12011)

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potiuk pushed a commit to branch v1-10-test
in repository https://gitbox.apache.org/repos/asf/airflow.git

commit 887c231332d2d425d7f81ba0973dc12c508d8a2c
Author: Ry Walker <42...@users.noreply.github.com>
AuthorDate: Sun Nov 1 12:34:34 2020 -0500

    Revise "Project Focus" copy (#12011)
    
    (cherry picked from commit 77ae32e311ebd9f6ab236cbeba42f7de3dd1e211)
---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index ccac802..70bf2d8 100644
--- a/README.md
+++ b/README.md
@@ -59,11 +59,11 @@ Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The
 
 ## Project Focus
 
-Airflow works best with workflows that are mostly static and slowly changing. When the structure is similar from one run to the next, it allows for clarity around unit of work and continuity. Other similar projects include [Luigi](https://github.com/spotify/luigi), [Oozie](http://oozie.apache.org/) and [Azkaban](https://azkaban.github.io/).
+Airflow works best with workflows that are mostly static and slowly changing. When DAG structure is similar from one run to the next, it allows for clarity around unit of work and continuity. Other similar projects include [Luigi](https://github.com/spotify/luigi), [Oozie](https://oozie.apache.org/) and [Azkaban](https://azkaban.github.io/).
 
-Airflow is commonly used to process data, but has the opinion that tasks should ideally be idempotent, and should not pass large quantities of data from one task to the next (though tasks can pass metadata using Airflow's [Xcom feature](https://airflow.apache.org/docs/stable/concepts.html#xcoms)). For high-volume, data-intensive tasks, a best practice is to delegate to external services that specialize on that type of work.
+Airflow is commonly used to process data, but has the opinion that tasks should ideally be idempotent (i.e. results of the task will be the same, and will not create duplicated data in a destination system), and should not pass large quantities of data from one task to the next (though tasks can pass metadata using Airflow's [Xcom feature](https://airflow.apache.org/docs/stable/concepts.html#xcoms)). For high-volume, data-intensive tasks, a best practice is to delegate to external servic [...]
 
-Airflow **is not** a streaming solution. Airflow is not in the [Spark Streaming](http://spark.apache.org/streaming/) or [Storm](https://storm.apache.org/) space.
+Airflow is not a streaming solution, but it is often used to process real-time data, pulling data off streams in batches.
 
 ## Principles