Use Azure Data Factory to orchestrate the data pipeline and leverage Azure Data Lake Storage Gen2 for storing the raw data, ensuring data privacy and security through encryption and access control.

Use Azure Databricks to process the data using its built-in support for Delta Lake, and integrate Jupyter notebooks for data exploration and analysis, while implementing data privacy and security measures.

Use Azure Stream Analytics to process the data in real-time and store the results in Azure SQL Database, ensuring data privacy and security through built-in features.

Use Azure Functions to process the data in small batches and store the results in Azure Cosmos DB, implementing data privacy and security through custom code.