Update concepts-data-flow-overview.md

Author: kromerm

articles/data-factory/concepts-data-flow-overview.md

@@ -64,9 +64,9 @@ If you put all of your logic inside a single data flow, ADF will all execute in
 
 This option can possibly be more difficult to follow and troubleshoot because your business rules and business logic will be jumble together. This option also doesn't provide much re-usability.
 
-##### Execute data flows serially
+##### Execute data flows sequentially
 
-If you execute your data flow activities in serial in the pipeline and you have set a TTL on the Azure IR configuration, then ADF will reuse the compute resources (VMs) resulting in faster subsequent execution times. You will still receive a new Spark context for each execution.
+If you execute your data flow activities in sequence in the pipeline and you have set a TTL on the Azure IR configuration, then ADF will reuse the compute resources (VMs) resulting in faster subsequent execution times. You will still receive a new Spark context for each execution.
 
 Of these three options, this will likely take the longest time to execute end-to-end. But it does provide a clean separation of logical operations in each data flow step.