Training Overview
Disclaimer: This course is independently developed and not affiliated with Microsoft. It covers concepts and skills that closely align with the objectives of Microsoft’s DP-700: Microsoft Fabric Data Engineer training, making it a strong preparatory or complementary learning experience.
Fabric Data Engineering Mastery: Building Scalable, Intelligent Data Workflows
This four-day advanced custom training, equips data professionals to architect and optimize complex data ecosystems using Microsoft Fabric. Participants will gain hands-on expertise in designing resilient pipelines, managing schema evolution, and enabling real-time processing across distributed systems. The goal is to transform raw data into a reliable, scalable asset for advanced analytics and AI deployment.
While not strictly required, participants will benefit from having a working knowledge of data engineering fundamentals, such as ETL processes, SQL, and cloud platforms like Azure. Familiarity with handling structured and unstructured data using tools like PySpark and KQL will enhance the learning experience. This course is designed to support a wide range of learners, especially those aiming to build scalable analytics solutions across modern data ecosystems.
Module Breakdown:
Ingest Data with Microsoft Fabric: Learn to connect and extract data from diverse sources using Dataflows Gen2, pipelines, and Spark notebooks. Apply transformations with Power Query and orchestrate ingestion workflows across OneLake.
Implement a Lakehouse in Microsoft Fabric: Build scalable lakehouse architectures using Delta tables and unified analytics engines. Explore schema evolution, data versioning, and hybrid querying with Spark and SQL.
Implement Real-Time Intelligence with Microsoft Fabric: Enable streaming ingestion and event-driven analytics using Eventstreams and KQL. Design dashboards and alerts for operational intelligence and anomaly detection.
Implement a Data Warehouse with Microsoft Fabric: Create dedicated SQL pools for structured data. Optimize performance with indexing, partitioning, and caching strategies to support BI and reporting workloads.
Manage a Microsoft Fabric Environment: Configure workspaces, capacities, and security roles. Monitor performance, troubleshoot workloads, and apply governance best practices for scalable analytics operations.