Microsoft Fabric: Ingest and Transform Data

О курсе

Welcome to Microsoft Fabric: Ingest and Transform Data, a hands-on course designed to help data professionals, engineers, and analytics practitioners build reliable and scalable data processing workflows in Microsoft Fabric. This course focuses on both batch and real-time data ingestion, transformation, and pipeline orchestration using Fabric components such as Eventstreams, KQL, Spark, Dataflows, and Pipelines. You’ll learn how to integrate structured and streaming data sources, apply data transformation logic, and prepare analytics-ready datasets for reporting and insight generation. Through guided demos and practical exercises, this course bridges the gap between data processing concepts and real-world implementation. This course delivers approximately 3+ hours of structured video instruction, combining conceptual foundations with hands-on demonstrations. The learning path is organized into two major modules, each focused on practical implementation techniques. To support reinforcement and skill retention, each module contains in-video checkpoints and short quizzes. Enroll in Microsoft Fabric: Ingest and Transform Data, and gain the practical skills needed to build data workflows that are reliable, real-time, and optimized for analytics and reporting. Course Modules: Module 1: Data Loading and Real-Time Processing in Microsoft Fabric. Learn how to design batch and streaming data loading patterns, ingest real-time data, perform filtering and aggregation, and create live dashboards using Fabric Eventstreams, KQL, and Spark. Module 2: Data Ingestion and Transformation in Microsoft Fabric. Build end-to-end data processing pipelines by choosing appropriate data stores, transforming data with PySpark/SQL/KQL, managing shortcuts, pipelines, mirroring, and applying data quality and governance techniques. By the End of This Course, You Will Be Able To: Design and implement performant batch and incremental data loading patterns in Microsoft Fabric. Ingest and process real-time streaming data using KQL, Eventstreams, and Spark Structured Streaming. Build complete data transformation pipelines using Dataflows, Notebooks, Mirroring, and Fabric Pipelines. Apply data transformation and quality techniques such as windowing, aggregation, deduplication, and denormalization. Deploy scalable, analytics-ready datasets for reporting, dashboards, and downstream insight generation. Who Should Take This Course? Data Engineers / Cloud Data Practitioners Power BI / Fabric Developers Data Analysts transitioning to end-to-end data workflows Professionals preparing for Microsoft Fabric certifications This course is designed for data professionals and cloud engineers looking to ingest, load, transform, and process data efficiently using Microsoft Fabric. You’ll explore how to build scalable data pipelines, integrate streaming and batch data sources, and perform real-time data processing using Fabric components such as Eventstreams, KQL, Spark, Dataflows, and Pipelines.

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