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Answer: Azure Databricks
Azure Databricks is an analytics platform optimized for Apache Spark, which provides a collaborative environment for data science and data engineering. It allows you to write custom data transformation logic using Spark's APIs in Scala, Python, R, Java, or SQL. This makes it an ideal choice for complex data transformations that require the power of Spark and the flexibility of custom code. While Azure Data Factory, Azure Stream Analytics, and Azure Functions can also be used for data transformation, they are more suited for specific use cases and may not provide the same level of flexibility and power as Azure Databricks.
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You are designing a data pipeline that requires the transformation of data from various sources into a unified format for analysis. Which Azure service would you use to create a custom data transformation logic and why?
A
Azure Data Factory with Data Flow activity
B
Azure Stream Analytics
C
Azure Databricks
D
Azure Functions