DP-900 Describe an analytics workload on Azure Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Azure Data Lake Storage Gen2

  Why it's wrong here

  Azure Data Lake Storage Gen2 is a hierarchical, blob-based storage service designed to hold massive amounts of structured and unstructured data as files. It provides the underlying storage layer for analytics workloads but lacks compute engines or pipeline capabilities to perform data transformations. While data can be read from and written to it by transformation services, it does not natively support any transformation logic itself.

• ✗

  Azure Event Hubs

  Why it's wrong here

  Azure Event Hubs is a real-time data ingestion and streaming platform that receives and processes millions of events per second from connected devices and applications. Its primary role is to collect, buffer, and deliver event streams to downstream consumers, not to reshape or enrich the data. It does not include built-in transformation features such as mapping data flows or scripted jobs, so it cannot be used to perform data transformation on its own.

• ✓

  Azure Data Factory

  Why this is correct

  Azure Data Factory is a cloud-based data integration service that enables the creation of ETL and ELT pipelines, orchestrating data movement and transformation across many sources and destinations. It offers Mapping Data Flows, which provide a visual, code-free interface for performing scalable transformations like joins, aggregations, and pivots, as well as the ability to call external compute services for more complex logic. This makes it a dedicated and correct choice for data transformation tasks.

• ✗

  Power BI

  Why it's wrong here

  Power BI is a business analytics and visualization tool used for creating interactive dashboards and reports, with Power Query and DAX allowing basic data shaping within its desktop application. However, its transformation capabilities are designed for in-memory report preparation rather than large-scale, server-side data processing or reusable pipeline transformations. Since Power BI is primarily for analysis and presentation, it is not a suitable service for performing general data transformation workloads.

• ✓

  Azure Databricks

  Why this is correct

  Azure Databricks is an Apache Spark-based analytics platform that offers a collaborative workspace for running data engineering and data science workloads. It supports complex data transformations through notebooks and Spark jobs, allowing code-first processing using Python, Scala, SQL, and R, plus streaming and batch data flows. This makes it a powerful, scalable service for performing transformation tasks, from simple cleanses to advanced machine learning preprocessing.

Go deeper

Related to this question