You have a requirement to use a data processing pipeline to process documents uploaded to Azure Blob Storage. Based on the solution requirements, you should be able to read the layout, extract the data in .csv format and execute reports on that data using Power BI. 
Assuming that you have Visual code with required extensions, python and storage explorer are installed. Which of the Azure services would you use in this solution other than Azure Blob Storage, Azure Table Storage and Power BI? (choose two options).

Answer options:

A.Azure Databricks
B.Azure Synapse
C.Azure Functions
D.Azure Form Recognizer
E.Azure Data Factory

Correct Answers: C and D
Option A is incorrect because Azure databricks are used for big data functions. Given the scenario, the solution cannot use this service to meet the requirements.
Option B is incorrect because Azure synapse is a data warehouse solution. It is not capable of recognizing the layout and extract data from the documents. You would need to form a recognizer service to meet the solution requirement.
Option C is correct because the Azure function would be triggered when a file is uploaded into the blob storage. That way, the documents can be parsed to the Form Recognizer API.
Option D is correct. Here are the steps involved in the process:
Create an Azure Storage account
Create an Azure Functions project
Extract layout data from uploaded forms
Upload layout data to Azure Storage
Option E is incorrect because the Azure data factory is a fully managed data integration solution for ingestion and transformation. However, it cannot read the document layout and extract the data from documents in the Blob Storage.
Reference:
To learn more about using the Azure function to process stored documents, use the link given below: 

https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/tutorial-azure-function?tabs=2-0