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Data Engineering Concepts in Microsoft Fabric Flashcards
Microsoft Fabric Data Engineer Associate DP-700 Flashcards
Study our Data Engineering Concepts in Microsoft Fabric flashcards for the Microsoft Fabric Data Engineer Associate DP-700 exam with 30+ flashcards. View as flashcards, a searchable table, or as a fun matching game.
| Front | Back |
| How does Microsoft Fabric enable data governance | Microsoft Fabric provides centralized management and policy enforcement to ensure compliance with organizational standards. |
| How does Microsoft Fabric ensure scalability | Microsoft Fabric offers cloud-native scalability leveraging Azure infrastructure. |
| How does Microsoft Fabric handle security | Microsoft Fabric uses Azure Active Directory for authentication and role-based access control for authorization. |
| How does Microsoft Fabric integrate with Power BI | Microsoft Fabric allows direct integration with Power BI for interactive data visualization and insights. |
| How does Microsoft Fabric optimize data storage | Microsoft Fabric uses intelligent caching and compression techniques to improve storage efficiency. |
| How does Microsoft Fabric support CI/CD pipelines | Microsoft Fabric integrates with Azure DevOps and GitHub for streamlined continuous integration and deployment workflows. |
| How does OneLake handle data compatibility | OneLake is compatible with multiple formats like Parquet, Delta, and CSV. |
| What are Data Pipelines used for in Microsoft Fabric | Data Pipelines are used for orchestration and scheduling workflows in Microsoft Fabric. |
| What are Dataflows in Microsoft Fabric | Dataflows enable self-service data preparation for use in Power BI and other Fabric components. |
| What are the major components of Microsoft Fabric | Data Factory, Spark, Data Engineering, Synapse Data Warehouse, Data Lakehouse, and Real-Time Analytics. |
| What are the supported data connectors in Microsoft Fabric | Microsoft Fabric supports connectors to various sources including Azure Blob Storage, SQL Server, and REST APIs. |
| What is a Lakehouse in Microsoft Fabric | A Lakehouse combines the capabilities of a data lake and a data warehouse within Microsoft Fabric. |
| What is Compute Scale in Microsoft Fabric | Compute Scale refers to the ability to dynamically adjust resources based on workload demands. |
| What is Delta Lake in Microsoft Fabric | Delta Lake is an open-source storage layer in Microsoft Fabric that supports ACID transactions and scalable metadata handling. |
| What is Direct Lake mode in Microsoft Fabric | Direct Lake mode allows queries to access data directly from OneLake without requiring data copies. |
| What is Microsoft Fabric | Microsoft Fabric is an end-to-end analytics solution for data engineering and data science tasks. |
| What is the benefit of OneLake in Microsoft Fabric | OneLake serves as the unified storage layer for data across Microsoft Fabric. |
| What is the benefit of using Git integration in Microsoft Fabric | Git integration enables version control and collaboration for code and workflow artifacts. |
| What is the benefit of using shortcuts in Microsoft Fabric | Shortcuts allow referencing data in OneLake across multiple workspaces without duplicating it. |
| What is the importance of workspace in Microsoft Fabric | Workspaces in Microsoft Fabric provide an organized environment for collaborating on data projects. |
| What is the purpose of Data Integration in Microsoft Fabric | Data Integration facilitates seamless connectivity across data sources for unified analytics. |
| What is the purpose of Synapse Data Warehouse in Microsoft Fabric | Synapse Data Warehouse supports large-scale relational data storage and enables high-performance analytics. |
| What is the role of Data Factory in Microsoft Fabric | Data Factory enables seamless data movement and orchestration of ETL workflows within Microsoft Fabric. |
| What is the role of monitoring in Microsoft Fabric | Monitoring ensures performance tracking, error identification, and real-time observability across data workflows. |
| What is the role of notebooks in Microsoft Fabric | Notebooks provide an interactive environment for analyzing and transforming data using code, such as Python and Scala. |
| What is the role of Spark in Microsoft Fabric | Spark enables distributed processing for big data tasks and supports integration with other Fabric components. |
| What programming languages can be used for Spark in Microsoft Fabric | Python, Scala, R, and SQL can be used for Spark in Microsoft Fabric. |
| What type of analytics does Real-Time Analytics focus on in Microsoft Fabric | Real-Time Analytics specializes in event-driven data processing for instant insights. |
| Why is ACID compliance important in Microsoft Fabric | ACID compliance ensures data reliability, consistency, and integrity. |
| Why is data lineage critical in Microsoft Fabric | Data lineage provides end-to-end traceability, aiding in compliance and data governance. |
About the Flashcards
Flashcards for the Microsoft Fabric Data Engineer Associate exam make it easy to review essential Microsoft Fabric terminology, core services, and architecture. Cards focus on concise definitions for components like Data Factory, Synapse Data Warehouse, Lakehouse, OneLake, Delta Lake, and Spark so you can quickly reinforce vocabulary and understand each service's purpose.
Use the deck to practice concepts such as data integration and orchestration, ETL pipelines, Spark processing and notebooks, storage formats and ACID transactions, compute scaling and performance, security with Azure Active Directory and role-based access, monitoring and data lineage, plus integration with Power BI, Azure DevOps, and Git for CI/CD.
Topics covered in this flashcard deck:
- Core Fabric components
- OneLake and Delta Lake
- Data pipelines and orchestration
- Spark and notebooks
- Security and governance
- Real-time analytics and Direct Lake