Microsoft Azure Data Engineer Associate - DP-203
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You are tasked with developing a batch processing solution for a financial services company that needs to process large volumes of trade data daily. The solution should be able to handle upserts, revert data to a previous state, and configure exception handling. Additionally, the company wants to integrate Jupyter or Python notebooks into the data pipeline for data exploration and analysis. How would you approach this task?
Explanation:
Option B is the most suitable approach as it leverages Azure Databricks for processing and analysis, and integrates Jupyter notebooks for data exploration. Azure Databricks provides built-in support for Delta Lake, enabling efficient upserts and data versioning. Additionally, Jupyter notebooks can be integrated into the data pipeline for further analysis. Options A, C, and D do not fully address the requirements of the task.