Create how-to-sqldb-to-cosmosdb

Author: kromerm

articles/data-factory/how-to-sqldb-to-cosmosdb

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+---
+title: Migrate Azure SQL Database tables to Azure CosmosDB with Azure Data Factory
+description: Take an existing normalized database schema from Azure SQL Database and migrate to CosmosDB denormalized collection with Azure Data Factory.
+services: data-factory
+author: kromerm
+
+ms.service: data-factory
+ms.workload: data-services
+
+ms.topic: conceptual
+ms.date: 04/29/2020
+ms.author: makromer
+---
+
+# Migrate normalized database schema from Azure SQL Database to Azure CosmosDB denormalized collection
+
+By using mapping data flows in Microsoft Azure Data Factory, you can transform data from fixed-width text files. In the following task, we'll define a dataset for a text file without a delimiter and then set up substring splits based on ordinal position.
+
+## Create a pipeline
+
+1. Select **+New Pipeline** to create a new pipeline.
+
+2. Add a data flow activity, which will be used for processing fixed-width files:
+
+    ![Fixed Width Pipeline](media/data-flow/fwpipe.png)
+
+3. In the data flow activity, select **New mapping data flow**.
+
+4. Add a Source, Derived Column, Select, and Sink transformation:
+
+    ![Fixed Width Data Flow](media/data-flow/fw2.png)
+
+5. Configure the Source transformation to use a new dataset, which will be of the Delimited Text type.
+
+6. Don't set any column delimiter or headers.
+
+   Now we'll set field starting points and lengths for the contents of this file:
+
+    ```
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    1234567813572468
+    ```
+
+7. On the **Projection** tab of your Source transformation, you should see a string column that's named *Column_1*.
+
+8. In the Derived column, create a new column.
+
+9. We'll give the columns simple names like *col1*.
+
+10. In the expression builder, type the following:
+
+    ```substring(Column_1,1,4)```
+
+    ![derived column](media/data-flow/fwderivedcol1.png)
+
+11. Repeat step 10 for all the columns you need to parse.
+
+12. Select the **Inspect** tab to see the new columns that will be generated:
+
+    ![inspect](media/data-flow/fwinspect.png)
+
+13. Use the Select transform to remove any of the columns that you don't need for transformation:
+
+    ![select transformation](media/data-flow/fwselect.png)
+
+14. Use Sink to output the data to a folder:
+
+    ![fixed width sink](media/data-flow/fwsink.png)
+
+    Here's what the output looks like:
+
+    ![fixed width output](media/data-flow/fxdoutput.png)
+
+  The fixed-width data is now split, with four characters each and assigned to Col1, Col2, Col3, Col4, and so on. Based on the preceding example, the data is split into four columns.
+
+## Next steps
+
+* Build the rest of your data flow logic by using mapping data flows [transformations](concepts-data-flow-overview.md).