DP-900 Describe an analytics workload on Azure Practice Question
Your organization has a data lake on Azure Data Lake Storage Gen2 containing petabytes of raw clickstream data. Data scientists need to run exploratory analysis using Python and Spark, but they are not experienced with cluster management or infrastructure. The IT team wants to minimize administrative overhead while providing a collaborative notebook environment. Additionally, the solution must integrate with Microsoft Purview for data cataloging and lineage. Which Azure service should you recommend?
⚠ Common exam trap
Candidates often choose Azure Synapse Analytics because it also supports Spark and notebooks, but they overlook that Databricks is purpose-built for collaborative data science with minimal infrastructure management, while Synapse is optimized for data warehousing and ETL workloads.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Databricks
Azure Databricks is the correct choice because it provides a fully managed, collaborative notebook environment optimized for Apache Spark, allowing data scientists to run Python and Spark-based exploratory analysis without managing clusters. It integrates natively with Azure Data Lake Storage Gen2 for accessing petabytes of clickstream data and supports Microsoft Purview for automated data cataloging and lineage tracking, minimizing administrative overhead.
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 Databricks
Why this is correct
Databricks provides a collaborative notebook environment, automated cluster management, and integrates with Microsoft Purview.
- ✗
Azure Data Science Virtual Machine
Why it's wrong here
DSVM requires manual setup and does not provide managed Spark or collaborative notebooks.
- ✗
Azure Synapse Analytics (Synapse Studio)
Why it's wrong here
Synapse Studio is more focused on SQL and data warehousing; Databricks is better for data science.
- ✗
Azure HDInsight (Spark cluster)
Why it's wrong here
HDInsight requires more manual cluster management and lacks a built-in collaborative notebook environment.
Go deeper
Related to this question
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Data Roles and Core Concepts
Key term
Data Lake Storage Gen2
Data Lake Storage Gen2 is a cloud-based storage service that combines a scalable data lake with enterprise-grade file system capabilities for big data analytics.
Key term
Azure Databricks
Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure that lets data teams prepare data, run machine learning models, and build data pipelines using a single workspace.
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