Implementing Analytics Solutions Using Microsoft Fabric — Question 87

You have a Fabric tenant that contains JSON files in OneLake. The files have one billion items.

You plan to perform time series analysis of the items.

You need to transform the data, visualize the data to find insights, perform anomaly detection, and share the insights with other business users. The solution must meet the following requirements:

• Use parallel processing.
• Minimize the duplication of data.
• Minimize how long it takes to load the data.

What should you use to transform and visualize the data?

Answer options

• A. the PySpark library in a Fabric notebook
• B. the pandas library in a Fabric notebook
• C. a Microsoft Power BI report that uses core visuals

Correct answer: A

Explanation

The PySpark library in a Fabric notebook is the best option as it supports parallel processing, which is crucial for handling large datasets like one billion items. It also allows for efficient data transformation and visualization without duplicating data. In contrast, the pandas library is not optimized for large-scale data processing, and while Power BI is great for visualization, it does not focus on data transformation in the same way as PySpark.