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Azure Databricks Flashcards

7 cards from real DP-900 practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

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  1. Which of the following best describes the primary use case for Azure Databricks in an enterprise data platform?

    Answer: Large-scale data engineering, machine learning, and collaborative analytics

    Azure Databricks is optimized for large-scale data engineering pipelines, machine learning workloads, and collaborative analytics using distributed Apache Spark computing.

  2. What is Databricks Runtime?

    Answer: A set of core components including Apache Spark and optimized libraries that run on Databricks clusters

    Databricks Runtime is the set of core software components (Apache Spark, Delta Lake, and optimized libraries) that run on Databricks clusters and are maintained by Databricks.

  3. How does Azure Databricks differ from Azure Synapse Analytics Spark pools?

    Answer: Azure Databricks is a standalone optimized Spark platform with advanced ML features, while Synapse Spark is integrated within a broader analytics workspace

    Azure Databricks is a purpose-built, optimized Apache Spark platform with advanced ML/AI capabilities and collaboration features, while Azure Synapse Spark pools are Spark integrated within Synapse's broader unified analytics workspace.

  4. Which Azure Databricks feature enables multiple teams across data engineering, data science, and business analytics to work together?

    Answer: Collaborative shared notebooks and workspace with role-based access

    Azure Databricks provides shared interactive notebooks and a unified workspace with role-based access control, allowing data engineers, data scientists, and analysts to collaborate effectively.

  5. What kind of data workloads is Azure Databricks designed to handle?

    Answer: Both batch and streaming large-scale data processing

    Azure Databricks supports both batch processing of large datasets and real-time streaming data processing using Apache Spark's Structured Streaming capabilities.

  6. What is the relationship between Azure Databricks and Apache Spark?

    Answer: Azure Databricks is a cloud-optimized platform built on and extending Apache Spark

    Azure Databricks was created by the founders of Apache Spark and is a cloud-optimized platform that builds on and extends Apache Spark with additional collaboration, performance, and management features.

  7. Which Azure service can Azure Databricks use for storing and sharing machine learning models in a governed registry?

    Answer: Azure Machine Learning model registry

    Azure Databricks integrates with Azure Machine Learning's model registry, allowing data science teams to register, version, and manage ML models in a governed central repository.