diff --git a/examples/vehicle-speed-downsample-iotdb/README.md b/examples/vehicle-speed-downsample-iotdb/README.md
index 92cc6b6..a83b6a8 100644
--- a/examples/vehicle-speed-downsample-iotdb/README.md
+++ b/examples/vehicle-speed-downsample-iotdb/README.md
@@ -1,5 +1,5 @@
 # VSS Vehicle.Speed down-sample example
-This is an example of using the Central Data Service Playground (CDSP) to perform transformations on timeseries data using the Apache IoTDB data store. It accurately down-samples a timeseries of pre-recorded high frequency VSS `Vehicle.Speed` data.
+This is an example of using the Central Data Service Playground (CDSP) to transform timeseries data using the Apache IoTDB data store. It accurately down-samples a timeseries of pre-recorded high frequency VSS `Vehicle.Speed` data.
 
 ## Logical Concept
 In a data centric architecture the data/information layers can efficiently support ETL/ELT (Extract, Transform, Load) style operations. Timeseries data can be efficiently stored and retrieved by a timeseries database for example. Some databases will also provide the transform operation. This frees developers to concentrate on data architecture, algorithm selection and business logic.
@@ -286,9 +286,9 @@ IoTDB>
 </details>
 
 #### Example query 2: Down-sample and store result in new timeseries
-IoTDB supports the INTO clause which stores the result in a new timeseries. This is very useful for internal ETL/ELT (Extract, Transform, Load) style operations. For example this could be used to prepare the end of day upload of data described in the [example scenario](#example-scenario-journey-analysis) at the start of this document.
+The IoTDB SQL syntax provides the `INTO` clause which stores the result in a new timeseries. This is very useful for internal ETL/ELT (Extract, Transform, Load) style operations. For example this could be used to prepare the end of day upload of data described in the [example scenario](#example-scenario-journey-analysis) at the start of this document.
 
-Extend the example 1 query to place the result in a new timeseries `speed_upload`:
+Extend the example 1 SQL query to place the result in a new timeseries `speed_upload`:
 ~~~sql
 select sample(`Vehicle.Speed`,'method'='triangle','k'='100') into root.test2(speed_upload) from root.test2.vin123test
 ~~~