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DP-900 Describe core data concepts Practice Question

You are designing a data lake architecture for a large enterprise. You need to organize data into zones (raw, curated, and analytics) and enforce data lineage tracking. Which Azure service should you use to catalog and govern the data?

⚠ Common exam trap

Test-takers frequently confuse data integration or analytics services (like Azure Data Factory or Synapse) with a dedicated governance and cataloging tool, assuming lineage tracking is a built-in feature of those services rather than a separate function provided by Microsoft Purview.

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

Microsoft Purview

Microsoft Purview is the correct choice because it is a unified data governance service designed specifically for cataloging data assets, tracking lineage across hybrid and multi-cloud environments, and enforcing data policies. Unlike the other options, Purview provides out-of-the-box lineage scanning, a business glossary, and automated classification, making it the appropriate tool for organizing data into zones and ensuring end-to-end lineage in a data lake architecture.

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 Synapse Analytics

    Why it's wrong here

    Azure Synapse Analytics is a cloud analytics service that combines data warehousing, big data processing, and data integration, enabling T-SQL queries and pipeline orchestration. While it is a powerful engine for analyzing large volumes of data, it does not offer a centralized metadata repository for cataloging data assets across an entire data estate. Synapse does not provide features like classification, glossary, or cross-source lineage, which are essential for a governance-focused data lake architecture.

  • Azure Data Factory

    Why it's wrong here

    Azure Data Factory (ADF) is an integration service that orchestrates and automates data movement and transformation through pipelines. Although it can display lineage for data flows within its own pipelines, that lineage is limited to ADF activities and does not extend to assets not touched by ADF. It lacks a data catalog, business glossary, and policy management capabilities, making it unsuitable for unified data governance and cataloging across the data lake.

  • Microsoft Purview

    Why this is correct

    Microsoft Purview is a unified data governance and cataloging service that automatically scans Azure, on-premises, and multi-cloud sources, building a data map of technical and business metadata. It provides a searchable catalog, sensitive data classification, glossary, and end-to-end lineage across various data processes. This makes Purview the correct choice for governing a data lake, ensuring data is discoverable, understandable, and compliant.

  • Azure Databricks

    Why it's wrong here

    Azure Databricks is an Apache Spark-based analytics platform used for data engineering, ETL, and machine learning, with its own cluster management and notebook environment. The recently introduced Unity Catalog provides governance, but it is scoped to Databricks workspaces and does not automatically scan other sources like files, databases, or services outside the Databricks environment. Therefore Databricks is not a centralized governance solution for the whole data lake architecture.

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