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Data Engineering Concepts in Microsoft Fabric Flashcards
Microsoft Fabric Data Engineer Associate DP-700 Flashcards
| 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. |
This deck covers foundational data engineering concepts specific to Microsoft Fabric, including understanding its architecture and core components.