Microsoft Fabric Interview Questions and Answers
Q 1 : What is Microsoft Fabric?
A: Microsoft Fabric is an end-to-end analytics platform from Microsoft that unifies data integration, data engineering, data warehousing, data science, real-time analytics, and Power BI into a single SaaS solution.
Q 2 : Why did Microsoft introduce Microsoft Fabric?
A: Microsoft introduced Fabric to reduce data silos and tool fragmentation by providing one unified platform for all analytics workloads.
Q 3 : Is Microsoft Fabric a SaaS or PaaS service?
A: Microsoft Fabric is a Software as a Service (SaaS) platform where infrastructure, scaling, and maintenance are managed by Microsoft.
Q 4 : What are the main components of Microsoft Fabric?
A: The main components are Data Factory, Data Engineering, Data Science, Data Warehouse, Real-Time Analytics, Power BI, and OneLake.
Q 5 : What is OneLake in Microsoft Fabric?
A: OneLake is a unified data lake in Microsoft Fabric that centrally stores all organizational data, similar to OneDrive for data.
Q 6 : How is OneLake different from Azure Data Lake Gen2?
A: OneLake is automatically provisioned and tightly integrated with Fabric workloads, while Azure Data Lake Gen2 requires manual setup and management.
Q 7 : What is a Lakehouse in Microsoft Fabric?
A: A Lakehouse combines data lake flexibility with data warehouse performance, enabling analytics on large-scale structured and unstructured data.
Q 8 : What is the difference between Lakehouse and Data Warehouse in Fabric?
A: Lakehouse supports Spark processing and flexible data formats, while Data Warehouse focuses on structured SQL-based analytics.
Q 9 : What is Microsoft Fabric mainly used for?
A: Microsoft Fabric is used for data ingestion, processing, analytics, reporting, and generating business insights.
Q 10 : Who should learn Microsoft Fabric?
A: Data engineers, data analysts, BI developers, data scientists, and freshers entering data roles should learn Microsoft Fabric.
Q 11 : Is Microsoft Fabric a replacement for Azure Synapse?
A: Microsoft Fabric enhances and unifies Azure Synapse capabilities but does not fully replace all Azure services.
Q 12 : What is Data Engineering in Microsoft Fabric?
A: Data Engineering focuses on transforming and processing large datasets using Spark and Lakehouse architecture.
Q 13 : What is Data Factory in Microsoft Fabric?
A: Data Factory is used for data ingestion and orchestration, enabling users to build ETL pipelines using low-code or code-based approaches.
Q 14 : How does data ingestion work in Microsoft Fabric?
A: Data ingestion happens through Data Factory pipelines, built-in connectors, batch processing, and real-time event streams.
Q 15 : What are pipelines in Microsoft Fabric?
A: Pipelines are workflows that automate data movement, transformation, and scheduling tasks.
Q 16 : What is a notebook in Microsoft Fabric?
A: A notebook is an interactive environment used for writing code, exploring data, and performing analytics tasks.
Q 17 : Which languages are supported in Fabric notebooks?
A: Fabric notebooks support Python, SQL, Scala, and Spark-based languages.
Q 18 : What is Apache Spark in Microsoft Fabric?
A: Apache Spark is a distributed data processing engine used for large-scale data transformation and analytics.
Q 19 : What is Data Science in Microsoft Fabric?
A: Data Science enables advanced analytics, experimentation, and machine learning model development within Fabric.
Q 20 : How does Microsoft Fabric support machine learning?
A: Fabric provides built-in ML tools, notebooks, and model lifecycle management features.
Q 21 : What is Real-Time Analytics in Microsoft Fabric?
A: Real-Time Analytics allows analysis of streaming and event-based data with low latency.
Q 22 : What is KQL in Microsoft Fabric?
A: KQL (Kusto Query Language) is used to query real-time, log, and streaming data efficiently.
Q 23 : What role does Power BI play in Microsoft Fabric?
A: Power BI acts as the visualization layer, enabling dashboards, reports, and interactive analytics.
Q 24 : What is Direct Lake mode?
A: Direct Lake mode allows Power BI to query data directly from OneLake without data duplication.
Q 25 : What are semantic models in Microsoft Fabric?
A: Semantic models define business logic, measures, relationships, and calculations for reporting.
Q 26 : How does Microsoft Fabric ensure data security?
A: Fabric uses role-based access control, encryption, and governance policies to secure data.
Q 27 : What is RBAC in Microsoft Fabric?
A: Role-Based Access Control (RBAC) manages user access permissions based on assigned roles.
Q 28 : What is the role of Microsoft Purview in Fabric?
A: Microsoft Purview helps manage data governance, lineage, compliance, and data discovery.
Q 29 : What file formats are supported in Microsoft Fabric?
A: Fabric supports Delta, Parquet, CSV, JSON, and Avro file formats.
Q 30 : What is Delta Lake in Microsoft Fabric?
A: Delta Lake provides ACID transactions, data versioning, and reliable storage for analytics workloads.
Q 31 : Can Microsoft Fabric handle real-time data?
A: Yes, Microsoft Fabric supports real-time data ingestion and analytics using event streams and KQL.
Q 32 : Is coding mandatory to use Microsoft Fabric?
A: No, Microsoft Fabric supports both low-code tools and advanced coding options.
Q 33 : What industries use Microsoft Fabric?
A: Industries such as finance, healthcare, retail, manufacturing, and IT services use Microsoft Fabric.
Q 34 : What are the key benefits of Microsoft Fabric?
A: Unified analytics, scalability, reduced complexity, faster insights, and cost efficiency.
Q 35 : What are the limitations of Microsoft Fabric?
A: It is cloud-dependent and requires proper licensing for full Power BI functionality.
Q 36 : Is Microsoft Fabric suitable for small businesses?
A: Yes, Microsoft Fabric is scalable and suitable for both small and large organizations.
Q 37 : What is the pricing model of Microsoft Fabric?
A: Microsoft Fabric follows a capacity-based pricing model with shared compute resources.
Q 38 : Is a Power BI license required for Microsoft Fabric?
A: Yes, a Power BI license is required for report creation and sharing.
Q 39 : Can Microsoft Fabric connect to on-premises data?
A: Yes, it connects to on-premises data using secure data gateways.
Q 40 : What skills are required to learn Microsoft Fabric?
A: Basic SQL, data fundamentals, Power BI knowledge, and optional Python or Spark skills.
Q 41 : Is Microsoft Fabric good for freshers?
A: Yes, Microsoft Fabric is beginner-friendly and offers strong career opportunities.
Q 42 : How long does it take to learn Microsoft Fabric?
A: A basic understanding can be achieved in 4–6 weeks with consistent practice.
Q 43 : What certifications are available for Microsoft Fabric?
A: Microsoft offers Fabric-related analytics and data engineering certifications.
Q 44 : What is the future scope of Microsoft Fabric?
A: Microsoft Fabric has a strong future due to rising demand for unified analytics platforms.
Q 45 : How does Microsoft Fabric improve performance?
A: Fabric improves performance through shared compute, optimized storage, and Direct Lake access.
Q 46 : Can Microsoft Fabric replace traditional BI tools?
A: Yes, in many modern analytics use cases, Microsoft Fabric can replace traditional BI tools.
Q 47 : What is the difference between Microsoft Fabric and Power BI?
A: Microsoft Fabric is the complete analytics platform, while Power BI is focused on visualization.
Q 48 : Does Microsoft Fabric support AI features?
A: Yes, Microsoft Fabric includes AI and machine learning capabilities.
Q 49 : Why should companies migrate to Microsoft Fabric?
A: Companies migrate to simplify architecture, reduce costs, and improve data-driven decisions.
Q 50 : Is Microsoft Fabric in demand in 2026?
A: Yes, Microsoft Fabric skills are highly in demand due to unified analytics and AI integration.
Advanced Microsoft Fabric Interview Questions
Q 51 : How does Microsoft Fabric differ architecturally from traditional Azure analytics services?
A: Microsoft Fabric provides a unified SaaS-based analytics architecture where storage, compute, security, and governance are centrally managed, unlike traditional Azure services that require separate configuration and integration.
Q 52 : What role does OneLake play in Microsoft Fabric architecture?
A: OneLake acts as a single, organization-wide data lake that stores all analytics data, eliminating duplication and enabling seamless data access across Fabric workloads.
Q 53 : How does shared compute work in Microsoft Fabric?
A: Microsoft Fabric uses a shared capacity model where compute resources are dynamically allocated across workloads like data engineering, warehousing, and Power BI to improve efficiency.
Q 54 : How does Microsoft Fabric reduce data duplication?
A: Fabric stores data once in OneLake and allows multiple workloads to access it directly, reducing the need for multiple copies of the same data.
Q 55 : What is Direct Lake mode and why is it important?
A: Direct Lake allows Power BI to query data directly from OneLake without importing it, significantly improving performance and reducing storage overhead.
Q 56 : How does Delta Lake enhance Microsoft Fabric reliability?
A: Delta Lake provides ACID transactions, schema enforcement, and versioning, ensuring reliable and consistent data processing in Fabric.
Q 57 : How does Microsoft Fabric handle metadata management?
A : Fabric maintains a unified metadata layer that keeps schemas, lineage, and permissions consistent across all analytics services.
Q 58 : How is data security implemented in Microsoft Fabric?
A: Security is enforced using role-based access control, encryption at rest and in transit, and integration with Microsoft Purview for governance.
Q 59 : How does Microsoft Fabric support multi-tenant environments?
A: Fabric isolates workloads at the capacity and workspace level, ensuring tenant-level security and performance isolation.
Q 60 : How does Fabric integrate data engineering and data warehousing?
A: Both workloads share the same storage and metadata in OneLake, enabling seamless transitions between Spark-based and SQL-based analytics.
Q 61 : How do you design a medallion architecture in Microsoft Fabric?
A: Data is organized into Bronze (raw), Silver (cleaned), and Gold (business-ready) layers using Lakehouse and Delta tables.
Q 62 : How does Spark in Microsoft Fabric differ from Azure Databricks?
A: Fabric Spark is tightly integrated with OneLake and Power BI, while Azure Databricks operates as a separate managed Spark platform.
Q 63 : How are incremental data loads handled in Fabric?
A: Incremental loads are implemented using watermark columns, Delta Lake merge operations, and pipeline scheduling.
Q 64 : How does Fabric manage schema evolution?
A: Fabric supports automatic schema evolution in Delta tables while enforcing schema validation to prevent data corruption.
Q 65 : How do you optimize Spark performance in Microsoft Fabric?
A: Performance is optimized using partitioning, caching, optimized file sizes, and efficient Spark configurations.
Q 66 : What are OneLake shortcuts and why are they useful?
A: Shortcuts allow Fabric to reference external data sources without physically copying data, reducing storage costs and latency.
Q 68 : How does Fabric handle large-scale data partitioning?
A: Fabric uses partitioned Delta tables and optimized storage layouts to improve query and processing performance.
Q 69 : How do you implement data quality checks in Microsoft Fabric?
A: Data quality checks are implemented using Spark validations, pipeline conditions, and monitoring dashboards.
Q 70 : How does Fabric support CI/CD for data engineering?
A: Fabric integrates with Git for version control, enabling automated deployment and environment promotion.
Microsoft Fabric – Most Repeated Interview Questions
Q 71 : What is Microsoft Fabric?
A: Microsoft Fabric is an end-to-end analytics platform that unifies data ingestion, engineering, warehousing, data science, real-time analytics, and Power BI into a single SaaS solution.
Q 72 : Why is Microsoft Fabric important?
A: Microsoft Fabric simplifies analytics architecture by reducing multiple tools into one platform, improving productivity, performance, and governance.
Q 73 : What are the core components of Microsoft Fabric?
A: The core components are Data Factory, Data Engineering, Data Science, Data Warehouse, Real-Time Analytics, Power BI, and OneLake.
Q 74 : What is OneLake in Microsoft Fabric?
A: OneLake is a centralized data lake that stores all organizational data and allows all Fabric workloads to access it without duplication.
Q 75 : How is Microsoft Fabric different from Azure Synapse?
A: Microsoft Fabric is a SaaS-based unified platform, while Azure Synapse requires separate configuration and management of multiple services.
Q 76 : What is a Lakehouse in Microsoft Fabric?
A: A Lakehouse combines data lake storage with data warehouse performance using Delta tables and Spark processing.
Q 77 : What is Data Factory used for in Microsoft Fabric?
A: Data Factory is used for data ingestion, orchestration, and building ETL/ELT pipelines.
Q 78 : What is Data Engineering in Microsoft Fabric?
A: Data Engineering focuses on transforming and processing large datasets using Spark and Lakehouse architecture.
Q 79 : What is the role of Power BI in Microsoft Fabric?
A: Power BI is the visualization layer used for dashboards, reports, and business insights.
Q 80 : What is Direct Lake mode?
A: Direct Lake mode allows Power BI to query data directly from OneLake without importing data, improving performance.
Q 81 : What file formats are commonly used in Microsoft Fabric?
A: Delta, Parquet, CSV, JSON, and Avro are commonly used file formats.
Q 82 : What is Delta Lake and why is it important?
A: Delta Lake provides ACID transactions, schema enforcement, and data versioning for reliable analytics.
Q 83 : Does Microsoft Fabric support real-time data?
A: Yes, Microsoft Fabric supports real-time data ingestion and analytics using event streams and KQL.
Q 84 : What is KQL in Microsoft Fabric?
A: KQL (Kusto Query Language) is used for querying streaming, log, and time-series data efficiently.
Q 85 : How does Microsoft Fabric handle security?
A: Security is managed using role-based access control (RBAC), encryption, and governance policies.
Q 86 : What is RBAC in Microsoft Fabric?
A: RBAC controls user access to data and resources based on assigned roles.
Q 87 : What is Microsoft Purview’s role in Fabric?
A: Microsoft Purview provides data governance, lineage tracking, classification, and compliance management.
Q 88 : Is coding mandatory to use Microsoft Fabric?
A: No, Microsoft Fabric supports both low-code tools and advanced coding using SQL, Python, and Spark.
Q 89 : What is the pricing model of Microsoft Fabric?
A: Microsoft Fabric follows a capacity-based pricing model with shared compute resources.
Q 90 : Is a Power BI license required for Microsoft Fabric?
A: Yes, Power BI licenses are required for creating and sharing reports.
Q 91 : Can Microsoft Fabric connect to on-premises data?
A: Yes, it connects to on-premises data using secure data gateways.
Q 92 : What skills are required to learn Microsoft Fabric?
A: Basic SQL, data fundamentals, Power BI knowledge, and optional Python or Spark skills.
Q 93 : Is Microsoft Fabric suitable for freshers?
A: Yes, Microsoft Fabric is beginner-friendly and in high industry demand.
Q 94 : What are the main benefits of Microsoft Fabric?
A: Unified analytics, reduced complexity, better performance, scalability, and cost efficiency.
Q 95 : Why are companies migrating to Microsoft Fabric?
A: Companies migrate to simplify data architecture, reduce costs, and enable faster data-driven decision-making.
Power BI Integration – Interview Questions & Answers
Q 96 : How does Power BI integrate with Microsoft Fabric?
A: Power BI is natively integrated with Microsoft Fabric and acts as the visualization layer, directly consuming data from OneLake, Lakehouse, and Fabric Data Warehouse.
Q 97 : What is the role of Power BI in Microsoft Fabric architecture?
A: Power BI provides dashboards, reports, and semantic models that sit on top of Fabric data sources to deliver business insights.
Q 98 : What is Direct Lake mode in Power BI?
A: Direct Lake mode allows Power BI to query data directly from OneLake without importing or duplicating data, improving performance.
Q 99 : How is Direct Lake different from Import mode?
A: Import mode loads data into Power BI memory, while Direct Lake reads data directly from OneLake.
Q 100 : What data sources can Power BI connect to in Microsoft Fabric?
A: Power BI can connect to Lakehouse, Data Warehouse, KQL databases, notebooks, and external sources through OneLake shortcuts.
Microsoft Fabric Interview Questions and Answers
Q 101 : How are semantic models stored in Microsoft Fabric?
A: Semantic models are stored centrally in Fabric and reused across multiple Power BI reports.
Q 102 : How does Power BI handle data refresh in Fabric?
A: In Direct Lake mode, refresh is minimal, while Import mode requires scheduled or manual refreshes.
Q 103 : How does Power BI integrate with Fabric Lakehouse?
A: Power BI connects directly to Lakehouse Delta tables for analytics and reporting.
Q 104: How does Power BI integrate with Fabric Data Warehouse?
A: Power BI connects to Fabric Data Warehouse using SQL endpoints for structured analysis.
Q 105 : How does Power BI support real-time analytics in Fabric?
A: Power BI integrates with KQL databases and streaming datasets to deliver real-time dashboards.
Q 106 : Can Power BI consume streaming data from Fabric?
A: Yes, Power BI can visualize streaming and event-based data through Fabric Real-Time Analytics.
Q 107 : How does Power BI work with CI/CD in Fabric?
A: Power BI artifacts can be version-controlled using Git integration and deployed across environments.
Q 108 : What are shared semantic models in Power BI Fabric?
A: Shared semantic models allow multiple teams and reports to use the same governed data model.
OneLake-Focused Interview Questions & Answers
Q 109 : What is OneLake in Microsoft Fabric?
A: OneLake is a unified, organization-wide data lake in Microsoft Fabric that stores all analytics data in a single location, acting as a “OneDrive for data.”
Q 110 : Why is OneLake important in Microsoft Fabric?
A: OneLake eliminates data silos, reduces duplication, and allows all Fabric workloads to access the same data seamlessly.
Q 111 : How does OneLake differ from Azure Data Lake Gen2?
A: OneLake is automatically managed and deeply integrated with Fabric workloads, while Azure Data Lake Gen2 requires manual setup and service-level integration.
Q 112 : How does OneLake reduce data duplication?
A: Data is stored once in OneLake and shared across data engineering, warehousing, Power BI, and data science workloads without copying.
Q 113: How does OneLake support multiple workloads in Fabric?
A: OneLake provides a common storage layer that can be accessed simultaneously by Spark, SQL, KQL, and Power BI engines.
Q 114 : Can OneLake access data outside Microsoft Fabric?
A: Yes, OneLake shortcuts can connect to external data sources like Azure Data Lake without data movement.
Microsoft Fabric Interview Questions and Answers
Q 115 : How does security work in OneLake?
A: OneLake uses Fabric workspace permissions, role-based access control, and data-level security to protect data.
Q 116 : How does OneLake integrate with Power BI?
A: Power BI connects directly to OneLake using Direct Lake mode, enabling fast queries without importing data.
Q 117 : What is Direct Lake mode and how is it related to OneLake?
A: Direct Lake mode allows Power BI to read data directly from OneLake, improving performance and reducing refresh times.
Q 118 : How does OneLake support data governance?
A: OneLake integrates with Microsoft Purview for data lineage, classification, discovery, and compliance.
Governance and Security – Interview Questions & Answers (Microsoft Fabric)
Q 119 : How does Microsoft Fabric handle data governance?
A: Microsoft Fabric handles data governance through centralized management, shared metadata, and integration with Microsoft Purview for data discovery, lineage, and compliance.
Q 120 : What is the role of Microsoft Purview in Fabric governance?
A: Microsoft Purview provides data cataloging, classification, lineage tracking, and compliance reporting across all Fabric workloads.
Q 121 : How is security implemented in Microsoft Fabric?
A: Security in Microsoft Fabric is implemented using role-based access control (RBAC), encryption at rest and in transit, and workspace-level permissions.
Q 123 : What is RBAC in Microsoft Fabric?
A: Role-Based Access Control (RBAC) defines who can view, modify, or manage data and resources based on assigned roles.
Q 124 : How does Fabric support column-level security?
A: Column-level security is implemented by restricting column access through semantic models and permission settings.
Q 125 : How does Microsoft Fabric ensure data privacy?
A: Data privacy is ensured through encryption, access controls, auditing, and compliance with Microsoft security standards.
Q 126 : How does Microsoft Fabric support compliance requirements?
A: Fabric supports compliance through auditing, access logs, data classification, and integration with compliance tools.
Q 127 : How does Fabric handle data lineage?
A: Fabric automatically captures data lineage across ingestion, transformation, and reporting layers using Purview.
Q 128 : How does governance improve data trust in Microsoft Fabric?
A: Governance ensures data accuracy, consistency, and accountability, improving trust across analytics teams.
Q 129 : Can governance policies be applied across multiple Fabric workloads?
A: Yes, governance policies apply consistently across data engineering, data warehousing, Power BI, and real-time analytics.