Hello @Rahi Jangle There are several transformation activities available in Azure Data Factory that you can use to replace the Data Flow activity.
For example, you can use the following activities to perform transformations on your data:
- HDInsight Hive activity
- HDInsight Pig activity
- HDInsight MapReduce activity
- Stored Procedure activity
- Data Lake Analytics U-SQL activity
- .NET custom activity
Each of these activities has its own set of capabilities and limitations. You can choose the activity that best fits your requirements.
To replace the Data Flow activity, you need to create a new pipeline and add the appropriate activities to it. You can use the Copy activity to copy data from your source to your destination, and then use the transformation activities to perform the required transformations on the data.
For example, you can use the HDInsight Hive activity to execute Hive queries on your own or on-demand Windows/Linux-based HDInsight cluster. You can use the HDInsight Pig activity to execute Pig queries on your own or on-demand Windows/Linux-based HDInsight cluster.
You can use the HDInsight MapReduce activity to run MapReduce programs on your own or on-demand Windows/Linux-based HDInsight cluster.
You can also use the Stored Procedure activity to execute stored procedures in Azure SQL, Azure Synapse Analytics, or SQL Server.
You can use the Data Lake Analytics U-SQL activity to run U-SQL scripts in Azure Data Lake Analytics.
You can use the .NET custom activity to run custom code in HDInsight or Azure Batch. Regarding the standard practice followed in the industry to replace Data Flow, it depends on the specific requirements and constraints of the project. However, using the appropriate transformation activity based on the requirements is a common practice. So you have many options here: