Rename

Author: jlian

articles/iot-operations/connect-to-cloud/concept-schema-registry.md

@@ -83,7 +83,7 @@ Delta:
 
 ### Generate a schema
 
-To generate the schema from a sample data file, use the [Azure IoT Operations Schema Generator](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
+To generate the schema from a sample data file, use the [Schema Gen Helper](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
 
 For a tutorial that uses the schema generator, see [Tutorial: Send data from an OPC UA server to Azure Data Lake Storage Gen 2](./tutorial-opcua-to-data-lake.md).
 

articles/iot-operations/connect-to-cloud/howto-configure-dataflow-endpoint.md

@@ -31,7 +31,7 @@ Use the following table to choose the endpoint type to configure:
 > [!IMPORTANT]
 > Storage endpoints require a [schema for serialization](./concept-schema-registry.md). To use dataflow with Microsoft Fabric OneLake, Azure Data Lake Storage, Azure Data Explorer, or Local Storage, you must [specify schema reference](./howto-create-dataflow.md#serialize-data-according-to-a-schema).
 > 
-> To generate the schema from a sample data file, use the [Azure IoT Operations Schema Generator](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
+> To generate the schema from a sample data file, use the [Schema Gen Helper](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
 
 ## Dataflows must use local MQTT broker endpoint
 

articles/iot-operations/connect-to-cloud/howto-create-dataflow.md

@@ -437,7 +437,7 @@ When using MQTT or Kafka as the source, you can specify a [schema](concept-schem
 If the source is an asset, the schema is automatically inferred from the asset definition.
 
 > [!TIP]
-> To generate the schema from a sample data file, use the [Azure IoT Operations Schema Generator](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
+> To generate the schema from a sample data file, use the [Schema Gen Helper](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
 
 To configure the schema used to deserialize the incoming messages from a source:
 
@@ -788,7 +788,7 @@ builtInTransformationSettings:
 If you want to serialize the data before sending it to the destination, you need to specify a schema and serialization format. Otherwise, the data is serialized in JSON with the types inferred. Storage endpoints like Microsoft Fabric or Azure Data Lake require a schema to ensure data consistency. Supported serialization formats are Parquet and Delta.
 
 > [!TIP]
-> To generate the schema from a sample data file, use the [Azure IoT Operations Schema Generator](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
+> To generate the schema from a sample data file, use the [Schema Gen Helper](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
 
 # [Portal](#tab/portal)
 

articles/iot-operations/connect-to-cloud/tutorial-opcua-to-data-lake.md

@@ -106,7 +106,7 @@ In the quickstart, the data that comes from the oven asset looks like:
 The required schema format for Delta Lake is a JSON object that follows the Delta Lake schema serialization format. The schema should define the structure of the data, including the types and properties of each field. For more details on the schema format, see [Delta Lake schema serialization format documentation](https://github.com/delta-io/delta/blob/master/PROTOCOL.md#schema-serialization-format).
 
 > [!TIP]
-> To generate the schema from a sample data file, use the [Azure IoT Operations Schema Generator](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
+> To generate the schema from a sample data file, use the [Schema Gen Helper](https://azure-samples.github.io/explore-iot-operations/schema-gen-helper/).
 
 For this tutorial, the schema for the data looks like this: