getting started with data factory

It sounds like you're looking to use Azure Data Factory to automate the process of extracting data using Power Query (M code) and then load that data into an on-premises SQL Server or potentially in the cloud. Azure Data Factory (ADF) is a cloud-based data integration service that allows you to create, schedule, and manage data pipelines for various data movement and transformation tasks. It's primarily used for ETL (Extract, Transform, Load) processes.

While Azure Data Factory is quite flexible, it might not be the best tool for running Power Query directly, as Power Query is typically used within tools like Power BI or Excel. However, you can achieve your goal using a combination of tools and services. Here's a high-level approach:

1. Data Extraction and Transformation:

   Since your data originates from Yahoo Finance and is processed through Power Query (M code), you might want to consider the following steps:

   • Create a script (Python or another suitable language) to extract data from Yahoo Finance.
   • Use Power Query in Power BI Desktop to process and transform the extracted data. You can create a query in Power BI using M code and apply the transformations you need.

2. Data Loading:

   Once you have the transformed data, you can proceed with loading it into your target database:

   • Use Azure Data Factory to create a data pipeline.
   • In the pipeline, you can have a Copy Data activity where you specify the source as the output of your Power Query transformation in Power BI.
   • For the destination, you can choose to land the data in an on-premises SQL Server or in the cloud-based SQL database, depending on your preference.

3. Azure Data Factory Mapping Data Flows (Optional):

   If you need more complex transformations beyond what Power Query can handle, you can use Azure Data Factory's Mapping Data Flows feature. This provides a visual interface for building data transformation logic without coding.

It's important to note that while Azure Data Factory can handle the data movement and orchestration part, Power Query itself might not be directly integrated into ADF. If you have complex transformations in your Power Query script, you may need to refactor or reimplement those transformations using the tools available in Azure Data Factory.

In summary, Azure Data Factory can help you automate the process of moving data between sources and destinations, but the direct integration of Power Query might require additional steps and considerations. Depending on your specific use case, you might also explore other Azure services like Azure Logic Apps or Azure Functions to handle the data transformation and orchestration aspects.